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Beschreibung

New technologies like blockchain and Internet of Things (IoT) are constantly improving the state-of-the-art in healthcare services. The trend of keeping medical records in digital formats is also increasing the reliance of modern healthcare service providers on these new technologies. This edited book brings a collection of reviews on blockchain and IoT technologies that are driving innovation in digital and smart healthcare systems. The editors bring an academic and practical approach to assist professionals and readers in understanding computerized healthcare solutions. 16 referenced chapters provide knowledge about fundamental framework, research insights, and empirical evidence for effective smart healthcare applications. The chapters also cover benefits and challenges of specific smart health frameworks, giving an informative overview of the subject.

Key themes of the book include:
1. Technological Foundations for Smart Healthcare
2. Blockchain Applications in Healthcare
3. Internet of Things (IoT) in Healthcare
4. Artificial Intelligence (AI) Integration
5. Security, Privacy, and Authentication
6. Medical Imaging and Deep Learning
7. Telemedicine

The content in the book is designed to help administrators and healthcare professionals to understand the basics of blockchain tech and IoT in smart healthcare systems and strengthen the competitive advantage of their clinics.

Readership
Healthcare professionals and administrators.

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Table of Contents
BENTHAM SCIENCE PUBLISHERS LTD.
End User License Agreement (for non-institutional, personal use)
Usage Rules:
Disclaimer:
Limitation of Liability:
General:
FOREWORD
PREFACE
List of Contributors
The Role of Emerging Technologies in Smart Health Care
Abstract
INTRODUCTION
Artificial Intelligence (AI)
INITIATIVES ON AI
Self-Diagnosis AI Apps
AI is a Useful Tool for Emergency Medical Personnel
Speeds Up the Invention and Improvement Of Genetic Remedy
AI in Pandemic
NANOTECHNOLOGY
How Nano-medicines or Smart Pills Work?
IoT
Five-Layer Architecture of IoT
Healthcare Monitoring Devices, Embedded Sensors
IoT Device Trends and Anticipated Growth
Key Market Insights
Drone
Transporting Devices and Materials
Enable Backup Transport System in the Pandemic
Delivering Organ Transfers
Blockchain
Machine Learning
CONCLUSION
REFERENCES
An Overview of Blockchain in the Field of Smart Healthcare System
Abstract
INTRODUCTION
MAJOR ISSUES AND CHALLENGES OF HEALTHCARE SYSTEMS
ROLE OF BLOCKCHAIN IN THE HEALTHCARE SYSTEM
BLOCKCHAIN APPLICATIONS IN HEALTHCARE
ROLE OF ARTIFICIAL INTELLIGENCE AND BLOCKCHAIN IN SMART HEALTHCARE SYSTEMS
RECENT CHALLENGES TO BLOCKCHAIN IMPLEMENTATION IN IN THE HEALTHCARE SYSTEMS
CONCLUSION AND FUTURE WORK OF BLOCKCHAIN IN THE FIELD OF SMART HEALTHCARE SYSTEMS
REFERENCES
Integration of Blockchain and Internet of Things
Abstract
INTRODUCTION
Blockchain
Components of Blockchain
Blockchain’s Features
Types of Blockchain
Internet of Things
Features of IoT System
Significant Utilization of IoT during the Covid-19 Pandemic
Integration of Blockchain and Internet of Things
Related Work
Research Challenges of IOT Data on Blockchain
Future Research Directions
i. Machine Machine Learning-Based Solutions for BIoT Applications' Security and Privacy
ii. Problems Arising from Decentralization's Technical Implementation
iii. Blockchain Infrastructure
iv. Governance, Regulations, and Legal Aspects
v. Adaptability
Conclusion and Future Work
REFERENCES
Consequences and Deliberations in Implementation of Blockchain and Internet of Things Integration
Abstract
INTRODUCTION
Literature Review
Types of Blockchain and Difficulties Faced while Implementing Blockchain Technology in IOT
Blockchain Types
a. Public Blockchain
b. Blockchain Consortium
c. Personalized Blockchain
i. The Transaction Between Performance, Power Consumption and Security
ii. Cooperating Between Throughput and Concurrency:
iii. Property Tests of IoT:
iv. Difficulties for Preserving Transparency and Confidentiality in IoT
v. Regulation and Difficulties of Blockchain Technology in IoT
Limitations and IOT Application Attacks
Limitations in IoT of Wireless Sensor
Blockchain Security Analysis
Improved Blockchain Security
Decentralization
Higher Traceability
Reduced Cost
Data Privacy
Immutability
Greater Transparency
CONCLUSION
REFERENCES
Blockchain Integrated with Internet of Things-benefits, Challenges
Abstract
INTRODUCTION
An Overview of the Internet of Things
IoT Features
Centralized Architecture of IoT
An Overview of Blockchain
Components of Blockchain
Design, Architecture and Methodology
Benefits and Applications
Benefits of Integrating IoT and Blockchain
Applications of Integration of IoT a Blockchain
Conclusion & Future Work
REFERENCES
Blockchain Powered Medical Sector – Application, Challenges and Future Research Scope
Abstract
INTRODUCTION
Components of Blockchain
Literature Review
Blockchain Technology in Medical Sector
Significant Applications Blockchain for Healthcare
Information Storage of a Patient
Analyse the Effects of a Particular Procedure
Validation
Safety and Transparency
Health Record Keeping
Clinical Trial
Display Information
Identification of False Content
Reduces Needless Overhead Expenses
Patient Monitoring
Create Research Initiatives
Maintain Financial Statements
Improves Safety
Reduce Data Transformation Time and Cost
Drug Traceability
Challenges in Healthcare Blockchain Adaptation
Data Collection and Storage
Data Sharing and Interoperability
The Need for a Socioeconomic Database
CONCLUSION AND FUTURE WORK
REFERENCES
Blockchain in the Healthcare Domain and Performing Various Security Analysis
Abstract
INTRODUCTION
LITERATURE SURVEY
PROBLEM STATEMENT
RESEARCH FRAMEWORK
IMPLEMENTATION
BitCoin Wallet
TESTING
RESULTS AND DISCUSSION
Summary of the Website
Website Screenshot
Exchange Spoof Attack
CONCLUSION AND FUTURE WORK
REFERENCES
IOT-Based Smart Healthcare System with Hybrid Key Generation and DNA Cryptography
Abstract
INTRODUCTION
Proposed Work
Key Generation Process
Encryption Process
Decryption Process
RESULTS AND DISCUSSION
CONCLUSION AND FUTURE WORK
REFERENCES
Security Enhancement in Cloud and Edge Computing Through Blockchain Technology
Abstract
INTRODUCTION
CLOUD COMPUTING
PRIVACY CHALLENGES IN CLOUD COMPUTING
Data Confidentiality Issues
Data Loss Issues
Geographical Data Storage Issues
Multi-Tenancy Security Issues
Transparency Issues
Hypervisor Related Issues
Managerial Issues
BLOCKCHAIN
Blockchain Introduces Benefits for Security and Privacy
Blockchain Research Areas from a Security and Privacy Perspective
Healthcare
Internet of Things
Vehicular Cloudlet
Payment and Loan
Privacy-Preserved Tracking
BLOCKCHAIN IN HEALTHCARE
Healthcare Implementation Using Blockchain
EDGE COMPUTING
APPLYING BLOCKCHAIN IN EDGE COMPUTING TO IMPROVE SECURITY AND PRIVACY
Anonymity
Authentication
Protocol Security
Security and Privacy in Architecture
Data Security
Integrity
Availability
User Privacy
ADVANTAGES OF COMBINING THE CLOUD COMPUTING NETWORK WITH BLOCKCHAIN TECHNOLOGY
Cloud Computing with Hyperledger Blockchains
Efficient Ownership Tracking
Decentralization
Increased Data Security
Fault Tolerance
Scalability
Faster Disaster Recovery
Micro Transactions
Distributed Supercomputing
Smartening Healthcare Sector
Smart Manufacturing
CONCLUSION AND FUTURE WORK
ACKNOWLEDGEMENTS
AUTHOR CONTRIBUTIONS
REFERENCES
Effective Automated Medical Image Segmentation Using Hybrid Computational Intelligence Technique
Abstract
INTRODUCTION
RELATED WORKS
DATABASE DETAILS
METHODOLOGY
RESULTS
CONCLUSION AND FUTURE WORK
References
IoT-Botnet Detection and Mitigation for Smart Healthcare Systems using Advanced Machine Learning Techniques
Abstract
INTRODUCTION
Background Methodologies
I. Botnet
II. DDoS attack
III. Security vulnerabilities in IoT
THEME OF WORK
LITERATURE REVIEW
PROPOSED DETECTION METHOD
A. ARCHITECTURE DIAGRAM
1. Collection of Dataset
2. Data Pre-processing
3. Feature Engineering
4. Training and Testing Data
5. Splitting of Data
B. SUPPORT VECTOR MACHINE
C. MULTI-LAYER PERCEPTRON (MLP) CLASSIFIERS
D. LIGHT GRADIENT BOOSTER MACHINE
E. PSEUDOCODE
PROPOSED APPROACH
RESULTS & ANALYSIS
Research Challenges Addressed
CONCLUSION & FUTURE WORK
REFERENCES
Smart Healthcare Classifier - Skin Lesion Detection using a Revolutionary Light Weight Deep Learning Framework
Abstract
INTRODUCTION
RELATED WORKS
DL Segmentation Techniques
METHODOLOGY
Number-theoretic First-order Cumulative Moment Algorithm
RESULTS AND DISCUSSION
CONCLUSION
REFERENCES
Recent Trends in Telemedicine, Challenges and Opportunities
Abstract
INTRODUCTION
TELEMEDICINE
HEALTHCARE
INDUSTRY SECTOR
MACHINE LEARNING
APPLICATIONS OF BIOMEDICAL SECTOR
CONCLUSION AND FUTURE WORK
REFERENCES
Sustainable Development for Smart Healthcare using Privacy-preserving Blockchain-based FL Framework
Abstract
INTRODUCTION
RELATED WORKS
PROPOSED METHODOLOGY
i. Methodology Used
ii. Modules Identified
iii. Modules For Framework Selection
iv. Modules For Privacy Preservation
v. Module For Communication Efficient
A). Dataset Description
B). Implementation: Module 1-FL with Flower Frame- work
I). ALGORITHM
Server
Client
II). Implementation
C). Module 2-FL with Pysyft Framework
I). ALGORITHM
II). Implementation
D). Module 3-FL with Secure Multiparty Computation
I). ALGORITHM
II). Implementation
E). Module 5: FL with Differential Privacy
I). ALGORITHM
II). Implementation
F). Mathematical Explanation
G). module 6: Communication Efficient Algorithm
I). ALGORITHM
II). Implementation
Evaluation and Analysis
A). Performance Evaluation
B). Attacks
CONCLUSION AND FUTURE WORK
REFERENCES
Smart Ambulance for Emergency Cases to be Reported to Hospitals at the Earliest using Deep Learning Algorithms and Blockchain-based Distri- buted Health Record Transactions for smart Cities
Abstract
INTRODUCTION
AI vs ML vs DL
BLOCKCHAIN
LITERATURE SURVEY
Call Systems During Emergency
Issues in Call Systems
Caller Location
Framework for Smart Ambulance System
IMPLEMENTATION METHODOLOGY
REST API SERVER
DATA EXTRACTION PHASE
RESPONSE AND DATA VISUALIZATION PHASE
CONCLUSION AND FUTURE WORK
REFERENCES
Authentication Techniques for Human Monitoring in Closed Environment
Abstract
INTRODUCTION
RADIO FREQUENCY IDENTIFICATION IN HUMAN MONITORING
SENSORS USED IN HUMAN MONITORING
PREDICTION PARAMETERS IN HUMAN MONITORING
DECISION-MAKING AND SEARCH IN HUMAN MONITORING
INFRASTRUCTURE OF THE CLOSED HUMAN MONITORING ENVIRONMENT
EXISTING TECHNOLOGIES AND TOOLS FOR HUMAN MONITORING
AUTHENTICATION TECHNIQUES IN HUMAN MONITORING SYSTEMS
CONCLUSION
REFERENCES
ABBREVIATION
Abbreviation
Blockchain and IoT based Smart Healthcare Systems
Edited by
L. Ashok Kumar
Department of EEE
PSG College of Technology
Coimbatore, Tamilnadu
India
D. Karthika Renuka
Department of IT
PSG College of Technology
Coimbatore, Tamilnadu
India
Sonali Agarwal
Department of IT
Indian Institute of Information Technology
Allahabad
India
&
Sheng-Lung Peng
College of Innovative Design and Management
National Taipei University of Business
Creative Technologies and Product Design
Taiwan

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FOREWORD

The Electronic Health Record (EHR) of a patient is a digitized document of their health history, progression comments, symptoms, and medications. Concerns about security abound, as they do with any online digital media. In the healthcare industry, the reliance on digital devices such as IoT, generates a massive volume of patient medical data. These EHR data statistics are confidential and cannot be made public. Medical data tampering can place a person's life in danger. Because of this, EHR information is subject to severe security and privacy risks. The high prevalence of health digital platforms presents a need for a more secure EHR system enabled by blockchain. Blockchain-based technologies have been proven and approved for delivering reliable and secure decentralised solutions to address the security and privacy threats associated with EHR data. Moreover, decentralized blockchain technology is unalterable. Preserving secrecy may allow for a more effective conversation between the physician and the patient, which is crucial for providing high-quality care. It also provides doctors, patients, and insurance providers an efficient way to obtain medical information while maintaining the privacy of the patient's data. The blockchain-based architecture provides the following features: privacy, authenticity, integrity, interoperability, and accountability of electronic health records between two entities. This book covers some state-of-the-art research associated with artificial intelligence, big data, and blockchain for smart health care development. It explains the fusion between the privacy and security of a blockchain-based data analytic environment. The book provides the fundamental framework, research insights, and empirical evidence for the efficacy of these new technologies, employing practical and basic approaches to help professionals and academics reach innovative solutions and grow competitive strengths.

V. Chandrasekar University Distinguished Professor and Associate Dean for International Programs Fellow IEEE, AGU, AMS, URSI and US national Academy of Inventors Colorado, State University Colorado, United States

PREFACE

Technology is constantly changing the healthcare industry, which is a crucial aspect of daily living. The use of technologies like Internet of Things (IoT), artificial intelligence, and blockchain systems can improve the state-of-the-art in health care and general medical practise. As the Internet of Things (IoT) has grown, its applications in the field of smart health care are adapted to various real-world scenarios. An Internet of Things (IoT)-based health care is a collection of intelligent medical tools and software that communicate online with a health care information system. It has created a world of opportunities in the medical industry. Smart connected medical gadgets can gather vital health information and offer additional information about the symptoms. Smart health care IoT devices range from basic wristbands that can track blood pressure, heart rate, and sleep patterns to linked inhalers, ingestible sensors, glucose monitors, and remote patient monitoring systems. These devices must have dependable connectivity and adhere to security and privacy laws in order to meet the demands of smart health care. A patient's medical information is kept digitally in a digital health record (EHR). The electronic health record (EHR) is a piece of technology that could provide the groundwork for new patient services and functionality. They increase patient access, raise the standard of service, and cut expenses. The blockchain security architecture assures that electronic health records between two organisations are confidential, authentic, legitimate, interoperable, and accountable. A blockchain-based approach to address the issues of data management, exchange, and storage, real-time patient monitoring at remote locations, monitoring of smart IoT devices, and faster and more seamless data transfer of patient medical records are just a few benefits that will come with the adoption of blockchain-based smart healthcare. Blockchain technology is a pervasive technology utilised in many industries, including banking, finance, supply chain management, and healthcare. The IoT and blockchain appear to be the ideal combination, as there is a great demand for data security given the volume of data generated by IoT sensors. A blockchain-enabled IoT-based smart health care is also an advancement because it can lessen the burden on healthcare systems and avoidable hospital visits by connecting patients with their health care providers and enabling the safe transfer and storage of medical data through the use of the blockchain mechanism. The book employs academic and practical approaches to assist professionals and academics in coming up with novel solutions and strengthening their competitive advantages. It provides the fundamental framework, research insights, and empirical evidence regarding the efficacy of these new technologies.

L. Ashok Kumar Department of EEE PSG College of Technology Coimbatore, Tamilnadu IndiaD. Karthika Renuka Department of IT PSG College of Technology Coimbatore, Tamilnadu IndiaSonali Agarwal Department of IT Indian Institute of Information Technology Allahabad India &Sheng-Lung Peng College of Innovative Design and Management National Taipei University of Business

List of Contributors

A. ValarmathiDepartment of Computer Applications Bit Campus, Anna University, Thiruchirappalli-24, IndiaAnand Kumar S.Vellore Institute of Technology, Vellore, IndiaAkila VictorSchool of Computer Science & Engineering, VIT, Vellore, IndiaChaithra V.BMS Institute of Technology and Management, Bengaluru, IndiaDivya PalanisamyN.G.P. Institute of Technology (affiliated to Anna University), NGP Nagar, Kalapatti -6410648, IndiaD. Karthika RenukaDepartment of IT, PSG College of Technology, Coimbatore, Tamilnadu, IndiaG. SrinivasaganDepartment of Chemistry, Rajapalayam Rajus College, Rajapalayam, Tamilnadu, IndiaGeeta Amol PatilBMS Institute of Technology and Management, Bengaluru, IndiaGeetha NarasimhanSchool of Computer Science & Engineering, VIT, Vellore, IndiaJaskiranjit KaurPanjab University, Chandigarh, IndiaJayashree K.Department of Artificial Intelligence and Data Science, Panimalar Engineering College, Chennai, IndiaKumaresan NatesanAnna University Regional Campus, Coimbatore, IndiaK. KarthigadeviDepartment of Computer Applications, Kalasalingam Academy of Research and Education, Krishnankoil, Tamilnadu, IndiaL. Ashok KumarDepartment of EEE, PSG College of Technology Coimbatore, Tamilnadu, IndiaM. NarayanaElectronics and Communication Engineering Department, Anurag University, Hyderabad, IndiaM. ShanmugananthamTamilnadu Government Polytechnic College, Tamilnadu, IndiaManoranjan DashDepartment of Artificial Intelligence, Anurag University, Hyderabad, IndiaPranshu TripathiSchool of Computer Science & Engineering, VIT, Vellore, IndiaParvesh KumarChandigarh University, Chandigarh, Punjab, IndiaPinaki Pratim AcharjyaDepartment of CSE, Haldia, Institute of Technology, Haldia -721607, IndiaPraveena VenkatesanNGP Institute of Technology, Coimbatore, Tamil Nadu 641048, IndiaPartheeban PonComputer Science and Engineering, Stella Mary's College of Engineering, Aauthenganvilai, Kanyakumari, IndiaPriya VijayDepartment of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, IndiaR. AnusuyaDepartment of IT, PSG College of Technology Coimbatore, Tamilnadu, IndiaR. ManimegalaiDepartment of Computer Science and Engineering, PSG Institute of Technology and Applied Research, Neelambur, Tamil Nadu 641062, IndiaRamya EaswaranSNS College of Technology, Coimbatore, IndiaR. NagarajanGnanamani College of Technology, Tamilnadu, IndiaRaghu IndrakantiElectronics and Communication Engineering Department, Anurag University, Hyderabad, IndiaR. BabuDepartment of Computational Intelligence, School of Computing, College of Engineering and Technology, SRMIST, Chennai, IndiaSurekha K.B.BMS Institute of Technology and Management, Bengaluru, IndiaSaranya RajendranSri Ramakrishna Engineering College, Coimbatore, Tamil Nadu 641022, IndiaSuresh Kumar NagarajanDepartment of Computer Applications, Kalasalingam Academy of Research and Education, Krishnankoil, Tamilnadu, IndiaSantanu KoleyDepartment of CSE, Haldia, Institute of Technology, Haldia -721607, IndiaS. JayanthiDepartment of Computer Science and Engineering, Bit Campus, Anna University, Thiruchirappalli-24, IndiaSanjay VasudevanSchool of Computer Science and Engineering, Vellore Institute of Technology, Vellore, IndiaSarvana Kumar SelvarajDepartment of Computer Science and Engineering, Jain University, Bangalore, IndiaS. KannadhasanStudy World College of Engineering Coimbatore, Tamilnadu, IndiaV. KavithaComputer Science and Engineering, University College of Engineering, Kancheepuram, IndiaVidhya E.Padmavani Arts and Science College for Women, Salem, Tamil Nadu 636011, IndiaV. VishuDepartment of Computer Applications, Coimbatore Institute of Technology, Coimbatore, Tamil Nadu 641014, IndiaVijay K.Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, IndiaYash VaishSchool of Computer Science & Engineering, VIT, Vellore, India

The Role of Emerging Technologies in Smart Health Care

Jaskiranjit Kaur1,*,Parvesh Kumar2
1 Panjab University, Chandigarh, India
2 Chandigarh University, Chandigarh, Punjab, India

Abstract

Numerous technological advancements like 3-D Printing, Virtual Reality (VR), Augmented Reality (AR), Artificial Intelligence (AI), Internet of Things (IoT), Drones, Robots, and Blockchain are now being inscribed for their ability to change the health care industry and make it a more automated and effective field. Various tools related to AI, like Google, DeepMind, Atomwise, Chatbot, Enlitic, Freenome, and Buoy Health, are helpful in makingthe health industry more efficient. There is another technology which is nanomicelle that can be used for effective drug delivery to treat various cancers, including breast, colon, and lung cancer. Moreover, self-assembling peptide nanoparticles that were prepared from SARSCov-1 spike (S) protein, successfully induced neutralizing antibodies against the coronavirus, subsequently preventing infection of Vero cells. Furthermore, the application of 3D printing in medicine can provide many benefits, including the customization and personalization of medical products, drugs, and equipment; cost-effectiveness; increased productivity; democratization of design and manufacturing; and enhanced collaboration. IoT enables real-time alerting, tracking, and monitoring, which permits hands-on treatment, better accuracy, apt intervention by doctors, and improves patient care delivery results. The other most promising application isblockchain in the healthcare sector for identity management, dynamic patient consent, and management of supply chains for medical supplies and pharmaceuticals. In addition, there are several case studies that describe the benefits of emerging tools, like recently the use of Emerging Technologies for the study, diagnosis, and treatment of patients with COVID-19 by using Deep Convolutional neural networks (CNN), which is a widely used deep learning architecture, enabled distinguishing between COVID-19 and other causes of pneumonia through chest X-ray image analysis.

Keywords: AI, Blockchain, Drone, IoT, Nanotechnology, Virtual reality.
*Corresponding author Jaskiranjit Kaur: Panjab University, Chandigarh, India; E-mail: [email protected]

INTRODUCTION

There are many technologies that are worthwhile in the healthcare sector, such as artificial intelligence (AI), bioprinting, nanotechnology, virtual reality, blockchain, and robotics. With the use of these technologies, anyone, anywhere at any time, might perform medicine in aneasy way, which makes the health industry more automated. In addition, with the use of emerging technologies, many other advantages are possible such as enabling remote monitoring of patients and their access to healthcare, health statistics collection, fast patient identification, access to medical records, and information exchange with providers and other patients.

Artificial Intelligence (AI)

Most of the AI and healthcare technologies have strong relevance to the healthcare field. Artificial intelligence in healthcare combines computer science and robust datasets to enable problem-solving related to health, such as patient care, diagnosing patients, end-to-end drug discovery and development, improving communication between physicians and patients, transcribing medical credentials, such as prescriptions, and remotely treating patients, administrative processes and helping them improve upon existing solutions and overcome challenges faster [1]. It also encompasses sub-fields of machine learning and deep learning, speech recognition, computer vision, and natural language processing which are frequently mentioned in conjunction with artificial intelligence to create expert systems that make predictions or classifications based on input data [2]. These learning algorithms evolve and become more accurate, they are likely to significantly impact healthcare services to identify diseases through diagnostic approaches, treatments, and care processes, and help develop more efficient and precise interventions. There are various tools that are based on AI to be helpful in the diagnosis of patients such as medical imaging technologies like computed tomography (CT), ultrasonography, x-rays, mammography, computed tomo- graphy (CT scans), nuclear medicine, and Magnetic resonance imaging (MRI) scan of human body parts.

INITIATIVES ON AI

A number of AI start-up companies like Google, Microsoft, and IBM have also been steadily increased investing in the development of health care with AI. There are several UK-based companies collaborating with UK universities and hospitals for better implementation of AI techniques. There are many Assisted Self-Diagnosis Apps that are based on AI methods, such as Ada, Babylon, Buoy Health, Your.MD, Mediktor, HealthTap, Apotheka Patient, Sensely, Health Buddy, etc.

Such paradigms are Harvard University’s teaching hospitals advancing health care systems with artificial intelligence techniques to diagnose potential blood diseases at a very early stage.

Self-Diagnosis AI Apps

BioXcel Therapeutics, a biopharmaceutical company, combines proprietary machine learning algorithms, big data, and AI techniques to find and develop novel therapeutics in the areas of immuno-oncology and the brain. Moreover, BioXcel's firm works with two drug re-innovation programs which are BXCL501 and BXCL701.

Buoy Health employs AI-based system algorithms to accurately identify, treat, and analyse signs of sickness. Chabot asks a patient about their symptoms and health concerns, then, after making a diagnosis, directs the patient to the appropriate care [3].

BERG is a biotech company in the trial stages that uses artificial intelligence and its own platform, Interrogative Biology, to change treatments for oncology, neurology, and uncommon diseases and map diseases. Critical biomarkers can be found in BERG, which speeds up the identification and development of therapies directed at the most promising therapeutic targets and pathways. The elimination of hit-to-lead optimization and screening in Berg's method, which generates virtual models of healthy and diseased cells, results in clear time-saving. Berg avoids these procedures by selecting compounds that occur naturally and using them as the foundation for medication in its virtual model [4].

XtalPi's ID4 platform combines AI technology, cloud, and quantum physics that provide small molecule candidate chemicals and pharmaceutical compounds for drug design and development in days instead of weeks or months for quick prediction and development by maintaining a petabyte-scale database consisting of pharmaceutically active molecules [5].

Deep Genomics' AI platform handles the complexity of RNA biology, identifies new targets, evaluates thousands of opportunities, increases the number of successful clinical trials, and accelerates time to market. It also identifies the best treatment candidates to increase and reduce costs. Moreover, over 69 billion dissimilar cell connections were analyzed by Deep Genomics' Project Saturn. Headquartered in New York, Kaia Health offers AI-powered digital therapy via a mobile app for exercise routines related to chronic pain, soporific events, and learning assets for the treatment of chronic low back pain, chronic bronchitis, and emphysema (COPD). We operate a digital treatment platform that we provide [6].

Analysis of Medical Imaging: The instrument of AI is utilized for case triage. It helps a doctor review scans and photos. In order to prioritize crucial cases, avoid errors while analyzing EHRs (electronic health records), and create more accurate diagnoses, radiologists or cardiologists might use this information.

Large amounts of data and photos from a clinical trial may need to be analyzed, so AI systems can quickly examine these datasets and relate data from other studies in order to find undetectable relationships and patterns. Medical imaging specialists can immediately track critical information. Patient Synopsis provides radiologists and cardiologists with a summary that focuses on the context of these images by delving into previous diagnostics and medical procedures, lab results, medical history, and known allergies [7].

Decrease the Cost to Develop Medicines: The effectiveness of possible medications for a variety of ailments has been predicted by supercomputers using databases of molecular structures. AtomNet's technology, convolutional neural networks, could predict the binding of tiny chemicals to proteins by examining cues from millions of experimental measurements and thousands of protein shapes. Convolutional neural networks were able to find a potential drug candidate that was both safe and effective using this technique, which decreased the cost of creating new medications.

In 2015, when the Ebola virus was outbreak in the West Africa, Atomwise with IBM and the University of Toronto worked together to find the best vaccine to stop the Ebola virus entry into body cells. The cure for the Ebola virus was made possible by this AI analysis, which was completed in less than a day instead of the typical month or year.

Analyzes Unstructured Data: Due to the vast volume of health data and medical records, clinicians frequently struggle to keep up with the most recent medical advancements while still providing high-quality patient-centered treatment. ML systems can swiftly scan EHRs and biomedical data organised by healthcare organizations and medical specialists to give clinicians timely, accurate answers. Health information and patient medical records are frequently kept as complex unstructured information, which makes them challenging to access and comprehend [8].

AI can find, gather, store, and standardize medical data, assisting with repetitive tasks and assisting clinicians with quick, precise, and customized treatment plans and medications for their patients instead of being overburdened with the burden of searching, identifying, gathering, and transcribing the solutions they need.

AI is a Useful Tool for Emergency Medical Personnel

The period between dialing 911 and the ambulance's arrival is crucial for recovery from a sudden heart attack. Emergency dispatchers must be able to recognise the symptoms of cardiac arrest in order to take the necessary action and increase the patient's chance of life. AI is capable of analyzing both verbal and nonverbal cues to establish a diagnosis remotely. An artificial intelligence tool called Corti helps emergency medical professionals. In order to determine whether a heart attack is occurring, Corti analyses the caller's speech, background noise, and pertinent data from the patient's medical records. In a heart attack, Corti alerts the appropriate authorities. Same as different ML tools, Corti no longer looks for specific signals; however, it trains itself by being attentive to many calls with a view to stumble on essential points. Corti continuously develops its version based on what it has learned. Approximately 73% of the time in Copenhagen, emergency dispatchers can identify a cardiac arrest based solely on the caller's description. However, AI can do higher. A small-scale look carried out in 2019 discovered that ML fashion had been capable of diagnosing cardiac arrest calls higher than human dispatchers through the usage of the speech reputation software app, ML, and different history clues. ML has a significant role to play in aiding emergency medical professionals. Future medical devices could leverage technology to send drones equipped with automatic defibrillators or trained volunteers to respond to emergency calls, increasing the chances of survival in cardiac arrests that happen in the community.

Speeds Up the Invention and Improvement Of Genetic Remedy

With the help of altered molecular phenotypes, such as protein binding, genetic disorders are preferred. Predicting those changes involves estimating the likelihood that hereditary diseases may develop. This is feasible with the aid of gathering information on all recognized compounds and biomarkers applicable to apply on scientific trials. This information is processed, for example, with the aid of using the AI gadget of Deep Genomics. The company develops its own proprietary AI and uses it to learn new ways to fix the effects of genetic mutations while developing specially crafted treatments for people suffering from rare Mendelian and complex diseases. The organisation exams recognized compounds to broaden a quicker genetic remedy for situations with excessive unmet needs. The organisation's professionals are running on “Project Saturn,” a drug gadget primarily based totally on AI molecular biology that assesses extra than sixty-nine billion oligonucleotide molecules in silico (carried out or produced through pc modeling or pc simulation) towards 1 million goal web sites for you to screen mobileular biology to free up extra ability remedies and cures. By lowering the

costs associated with treating rare illnesses, the development of genetic medicine benefits both patients and medical professionals.

AI in Pandemic

It checks the improvement of COVID-19 patients and shares patient information to make the surgeon’s job easy. This helps to manage the emergency condition of the patient by demonstrating several intelligent approaches. It alerts the patient to take proper medication through the utilization of the app. This technology performs the required medical tasks with less involvement of humans. It allows us to follow more critical aspects of patient care. AI-enabled robots are used for the communication of COVID-19 patients without the physical presence of doctors. The major roles of AI during the COVID-19 pandemic are contact tracing, preventing the spread of the COVID-19 virus, better understanding the nature of this virus, fever detection, predicting future outcomes, proper management of COVID-19 cases, controlling misinformation, vaccine development, detecting the probability of symptoms and proper surveillance systems [7]. It is used for the assessment of patient images and helps to predict the results. In the upcoming days, AI will provide an excellent source to identify problems and reduce the shortage of doctors. Some AI-related tools are summarized in Table 1.

Table 1AI tools and description.ToolsDescriptionGoogle DeepMindProcess CT and MRI scans, detect malignant cells, and other medical data to find novel, simple ways to diagnose and treat disease.AtomwiseUsed to develop effective medicines by analysing billions of chemicals and conducting preclinical drug trials.ChatbotListens to a patient’s symptoms and health concerns, diagnosis and then guidelines [50].EnliticTools to streamline radiology diagnosis, and it works to analyzing unstructured medical data.FreenomeBlood tests, diagnostic procedures, and screenings are used to detect cancer at an early stage and provide more effective therapy.Buoy HealthAI-based symptom and cure checker that uses algorithms to diagnose and treat illness

NANOTECHNOLOGY

Nanotechnology is a branch of technology that studies materials of extremely small structures, having a size of 0.1 to 100 nm. The use of nanotechnology widely ranges from industrial and medicinal to energy use due to its unique properties such as high photostability, high level of brightness, and absorption coefficients [9]. Moreover, these materials include more durable construction materials, effective bioavailability, minimal side effects, therapeutic drug delivery, and higher-density hydrogen fuel cells that are environmentally friendly and less costly. Nanotherapeutics and nanomedicines are available for clinical use, including treatments for cancer, high cholesterol, autoimmune diseases, fungal infections, macular degeneration, hepatitis, and many other conditions. Doxorubicin HCl liposome injection (Doxil, Ortho Biotech) for ovarian cancer, daunorubicin citrate liposome injection (DaunoXome, Diatos) for advanced AIDS-related Kaposi's sarcoma, and amphotericin B liposome injection (AmBisome, Gilead) for fungus infections are among the nanomedicines currently available on the market. The following Table 2 describes the Approved Cancer Drug Therapies Based on Nanotechnology [10].

Table 2Drug name and its description.Drug nameWhere it is usedIrinotecanTo treat colon or rectal cancer (cancer that begins in the large intestine)PaclitaxelTo treat breast cancer, ovarian cancerDoxorubicinTo treat cancer of the blood, lymph system, bladder, breast, stomach, lungsCimziaTo reduce pain and swelling due to certain inflammatory conditions [2]RapamuneTo prevent organ rejection after transplantation [2]EmendTo prevent nausea and vomiting that may be caused by chemotherapy [2]CabenuvaTo help control HIV infection

How Nano-medicines or Smart Pills Work?

Nano-medicines use smart nanoparticles for better drug delivery. Such systems are embedded with technological components such as microchips, cameras, or sensors that wirelessly communicate with wearable software or mobile apps and send information to computers at pharmacies or doctor’s offices. This technology diagnoses similar data as conventional diagnostic techniques such as endoscopy.

A brief explanation of the pharmaceutical nanosystem is as follows which is mentioned in Fig. (1):

Fig. (1)) Pharmaceutical Nano System.

As shown in the schematic diagram, pharmaceutical nanotechnology is divided into two basic types, which are nanomaterials and nanodevices.

Nanomaterials are materials of which a single unit is sized (in at least one dimension) between 1 and 100 nm and its some chemical properties include composition, structure, molecular weight, boiling and melting points, vapor pressure, octanol-water partition coefficient, water solubility, reactivity, and stability that are important in characterizing materials. These materials may be in the form of particles, tubes, rods, or fibres. Further, nanomaterails are categories of nanocrystalline and nanostructures. These nanostructures may be in the form of polymers or nonpolymers according to their properties. Nanostructured polymers may be nanoparticles, micelles, and drug conjugates, and nonpolymers are carbon nanotubes, silica nanoparticles, quantum dots, etc [12].

A nanocrystalline (NC) material is a polycrystalline material with a crystallite size of only a few nanometers and mostly used for treating wounds, especially burns and chronic wounds due to its effective antimicrobial properties. Other properties of nanocrystalline materials like increased strength/hardness, enhanced diffusivity, improved ductility/toughness, reduced density, reduced elastic modulus, higher electrical resistivity, increased specific heat, higher thermal expansion coefficient, and lower thermal conductivity make them more effective than conventional polycrystalline coarse-grained materials.

Nanodevices, including high electron mobility transistors, heterojunction bipolar transistors, resonant tunnelling diodes, and quantum optoelectronic devices like lasers and detectors, are also part of nanotechnology. Some nanodevices with their uses are described briefly in Tables 3 & 4.

Table 3Uses of Nanodevices.PillCamThe most recent PillCam model can take over 50,000 photos in a 12-hour period by shooting two to six frames per second. UT Southwestern began using PillCam technology in 2005 for diagnosing inflammation and pre-cancerous or dilated veins in the esophagus [3].Atmo Gas CapsuleAtmo Gas Capsule sensors can help detect the levels of oxygen and carbon dioxide in the body and any harmful substances. Additionally, it is utilised to track food sensitivity, find cancerous digestive organs, and diagnose gastrointestinal illnesses. The improved signal-to-noise ratio of the capsule as compared to breath testing is caused by the fact that gas concentrations in the gut are 5,000–10,000 times higher than those in the breath [4].Intelligent Sensor CapsulesEliminates the necessity for stomach injection of medications. When administered orally, it unfolds before settling on the organ, tracking vital signs for diagnostic and therapeutic vigilance.NanoFlaresNanoFlares are small, light-emitting particles that are made to bind to specific genetic targets in cancer cells, aiding in the detection of these cells. Exospores of the nanoscale are being collected and analysed by UC San Diego researchers in order to look for biomarkers for pancreatic cancer [5].NanobotsThe magnitude of a nanobot is smaller than a human cell in the field of medicine to deliver drugs, operate on internal injuries, and even combat cancer. These tiny bots are controlled by precise magnetic fields generated by an array of electromagnets and used to collect tissue biopsies or carry drug capsules inside the body [5].NanoSENSENanowear, the leading nanotechnology-based connected-care, and remote monitoring platform, today announced the clinical launch of NanoSENSE, a Heart Failure Management and Alert Diagnostic Validation Study. The unique and exceptional properties of nanomaterials (large surface area to volume ratio, composition, charge, reactive sites, physical structure, and potential) are exploited for sensing purposes.
Table 4List of nano mission sanctioned new projects for fy 2018-2019.S no.Project nameDate of Sanction1.Development of Nanoconjugates for site-specific delivery of Curcumin and siRNA to lung Cancer cells [6].21.02.20192.Development of a vesicular stomatitis virus glycoprotein based virus-like nanoparticles platform for targeted drug deliver [6].11.02.20193.Nanoscale interfacial magnetic skyrmion and its applications in memory devices [7].04.02.20194.Electric field-controlled spin dynamics in nanomagnets [6].14.01.20195.Nanostructured cathodes and Interlayers for Na-S and Mg-S batteries [6, 7].11.01.20196.Emergent electronic phases by interface and lattice engineering of complex oxides [6].11.01.20197.Investigations of organic nano- materials memory applicatons [6]28.02.2019

IoT

The Internet of Things (IoT) is a network of wireless systems that are connected to one another and networked digital devices like sensors and internet devices that can collect, send, and store data without the assistance of a human or computer [18], as shown in Table 5.

The Internet of Things (IoT) promises a number of benefits for streamlining and enhancing the delivery of healthcare, including the capacity to diagnose, treat, and monitor patients both within and outside of hospitals. There are more such advantages of using IoT like remote monitoring, medical data accessibility, improved treatment management, and instant and reliable treatment [19]. In 2022, during the pandemic period, IoT's sensor-based technology has the potential to lower the danger of surgery in difficult instances, which could be useful in COVID-19 [20-22]. In the medical field, IoT’s focus is to help perform the treatment of different COVID-19 cases precisely. By 2025, 75 billion IoT devices are anticipated to exist [22-24].

Table 5IoT integrated with other techniques.IoT integrated with other techniquesBenefits5G-IoT communicationThe upcoming 5G network is anticipated to serve smart healthcare applications that can generally meet the requirements, such as ultra-low latency, high bandwidth, ultra-high reliability, high density, and high energy efficiency. In order to enhance network performance, increase cellular coverage, and address security-related challenges, future smart healthcare networks are projected to integrate 5G and IoT devices. Speed up the system which is 100 times faster than the 4G network and it improves communication in the system [8].AI- IoTManage, analyze, and obtain meaningful insights from data with fast and accurate analysis. It tends to improve the quality and effectiveness of the specific service offered by integrating AI-driven IoT and tools with data mining features into individual medical devices [9].IoT with blockchainprevent unscrupulous attackers from accessing the network and make it more secure to ensure data integrity and availability. It is a threat breaker for computerized medical records [10].IoNT(nanotechnology)By integrating nano-communication capabilities with nano devices and enabling them to smoothly communicate with current micro- and macro devices, as well as by overcoming a number of other technological challenges, the IoNT vision may be fulfilled. Healthcare has resulted in more personalized, timely, and convenient health monitoring and treatment [11].cloud-based IoTThe main benefits are device connection management, secure device connection, data transfer and access control, real-time data management, and rich analytics and insights are easier than ever [12].

Five-Layer Architecture of IoT

All IoT-related services inevitably follow five basic steps called create, communicate, aggregate, analyze, and act. All these are done by some specific layer and each layer transfers data to the next layer in a meaningful way [25]. These 5 layers are as followed:-

The perception layer is the lowest layer of the conventional architecture of IoT and is called the recognition layer, which includes sensors (Humidity Sensors, Pressure Sensors, Proximity Sensors, and Level Sensors) for perceiving and acquiring environmental data and transform them in a digital setup [25, 26].

The transport layer is the next layer of IoT architecture which mainly focuses on transferring end-to-end sensor data from the perception layer to the processing layer and vice versa through networks such as wireless 3G, LAN(Local Area Network), Bluetooth, RFID (Radio-frequency identification), and NFC (Radio-frequency identification) with reliability, congestion avoidance. Ordering of packets, error detection, and correction in the delivery of data packets are the other main functions which this layer performs [26].

The Processing Layer is referred to as the IOT system's middleware layer. It stores, analyzes, and processes large amounts of data that come from the upper layer, that is, the transport layer. It is capable of managing and giving the lower layers a wide range of services [26, 27]. It makes use of a variety of technologies, including big data processing modules, cloud computing, and databases.

The Application Layer is responsible for delivering application-specific services to the clients with their prior requests. It describes several applications for the Internet of Things, such as smart homes, smart cities, and smart health.

The Business Layer oversees the entire Internet of Things (IoT) system, including all apps, business and revenue models, and user privacy, and it produces data-driven decision-making analysis. It is the most upper layer of IOT which interacts with the user [25]. All layers are shown in stack form in Fig. (2).

Fig. (2)) Architecture of IoT.

Sensors and Actuators: Context awareness is one of the key components of the Internet of Things and is impossible without sensor technology, and these IoT sensors are mostly capable of wired and wireless transmission, providing real-time, continuous data feed from assets and processes [28-30]. They increase accuracy while also ensuring faster transmission of measurement data, which enhances process control and asset health [31, 32].

Healthcare Monitoring Devices, Embedded Sensors

Table 6Embedded Sensors in Health Devices.SensorsWorking of sensorsGlucose monitoringGlucose monitoring is wearable technology that makes it easier to track your blood sugar levels over time by inserting the sensor properly under your skin, usually on your belly or arm [13].Heart-rate monitoringSensors integrated into a smartwatch or wearable like a ring, necklace, earbud, shoe, or item of clothing, many modern heart rate monitors are quite accurate [14].Hand hygiene monitoringSensors embedded help in hand hygiene is one of the most effective ways of reducing the transmission of pathogens that cause healthcare–associated infections [15].Depression and mood monitoringThe wristband that monitors for symptoms of a panic attack. When an imminent attack is detected, the 'Breathe Watch' alerts the wearer and/or their carers, and provides calming techniques [16].Connected inhalersDigital inhalers or smart inhalers embedded with sensors are used to collect, rescue, and control data virtually and in real-time, track adherence, and often include clinical platforms that aid patient self-management [16].Ingestible sensorsThe pill broadcasts a real-time video stream as it goes down your oesophagus and into your stomach [17].Gyroscope sensorsThey are also used in medical devices used to assist with the diagnosis, prevention, monitoring, and treatment of a disease or injury.

IoT Device Trends and Anticipated Growth

The estimations for the future growth of IoT devices have been fast and furious. One of the fastest-growing segments of the IoT market is healthcare devices, as shown in Table 6. In fact, it is anticipated that the market for this industry, commonly referred to as the Internet of Medical Things (IoMT), will reach $176 billion by 2026 [33].

According to Intel's predictions, the number of internet-enabled gadgets would increase from 2 billion in 2006 to 200 billion by 2020, or approximately 26 smart devices for every person on Earth.IHS Mark predicted that there will be 75.4 billion connected devices in 2025 and 125 billion by 2030, which is a little more conservative.

Other businesses have adjusted their statistics by excluding PCs, tablets, and smartphones from the calculation. By 2020, 20.8 billion connected things are predicted to be in use by Gartner, IDC, and BI Intelligence, respectively [33].

IDC forecasts that spending on IoT devices and services will total $772.5 billion in 2018, up 14.6 percent from the $674 billion it predicted would be spent in 2017, and then $1 trillion and $1.1 trillion in 2020 and 2021, respectively. Total spending on IoT devices and services was estimated by Gartner to be close to $2 trillion in 2017.

The Global IoT estimation was USD 72.91 billion in 2020 and is expected to reach USD 89.40 billion in 2021, projected to grow at a CAGR of 22.95% reaching USD 251.90 billion by 2026 in Healthcare Market size.

In 2020, COVID-19 is anticipated to be the third most common cause of mortality in the country, and the pandemic is anticipated to result in a deficit of 3.3 trillion dollars, or around 15% of GDP [33].

Virtual Reality (VR): Virtual reality (VR) is a simulated reality created by computer techniques to make a user completely immersed in a digital environment, and this environment is perceived through a device known as a Virtual Reality headset or helmet [34]. Virtual technologies can replicate various sensations, including vision, hearing, smelling, and even touching and other behaviours. Additionally, research from Statista indicates that the AR/VR market share would be approximately 193 billion dollars, or nearly 16 times what it was in 2018, As shown in Fig. (3).

Fig. (3)) VR healthcare market size.

Key Market Insights

According to our analysis, the global market for virtual reality in healthcare grew by an average of 36.0 percent in 2020 compared to 2019. In 2021, the market for virtual reality (VR) in healthcare was estimated to be worth USD 459.0 million. The market is anticipated to increase by USD 6.20 by 2029, representing a CAGR of 38.7% over the forecast period, from USD 628.0 million in 2022. By 2025, NewGenApps, a provider of AI, machine learning, big data analytics, and AR/VR solutions, predicts that 216 million people will be playing AR and VR games worldwide [35, 36].

Some of the most practical and pioneered ways virtual reality tools are helpful in the healthcare field are the following:-

1. Treatment in a VR Clinic:- Treatment for specific illnesses like phobias (flying, driving, public speaking, etc.), PTSD from car accidents, panic disorder, and agoraphobia is made simple or even possible due to VR Clinics. The skill to conduct the exposure session in a virtual environment, allowing for the stimulation of multiple senses (visual, auditory, and tactile), while still enabling the monitoring of the patient's physiology, allowed therapy to advance more quickly and, in the majority of cases, more successfully [37].

For instance, Cambridge University researchers developed and used a navigation test that employs virtual reality to identify individuals with early Alzheimer's disease and is more accurate than a traditional cognitive evaluation.

Phobia patients are treated by cognitive behavioral therapy in VR Clinic to recognize the thoughts causing negative feelings surrounding their fears and through thoughts, the patient learns how to replace those undesirable beliefs with more positive ones with fear in a controlled way and in small doses. By taking small steps, they can confront and gradually conquer their phobia.

2. Surgical Training:- Virtual reality enables cost-effective practice of practical skills without having to deal with consequences in real life. Due to the realistic graphics and feedback, it has used simulation as well as other technologies and procedures to attain an incredibly high bar for safety and give students a beneficial learning experience. After passing the VR training, healthcare professionals report improved accuracy and confidence when dealing with high-risk conditions for patients. As a result, specialised VR training platforms, such as OssoVR, Google VR, SteamVR, and Cluster, are enabled for more frequent and routine practise of various surgical operations with changeable settings and pre-set scenarios to develop skills and learn from mistakes [38, 39].

3. Dentistry treatment:- Virtual reality (VR) and augmented reality (AR) have many uses in the field of dentistry such as relaxation and pain management, preparing for a dental procedure in advance, and the best way to give training.VR tools enable dentists to practice their skills on virtual patients or even 3D models of teeth through special drills configured to imitate real-life tactile feedback. In place of the traditional teaching method using mannequins with plastic teeth, hapTEL, an example of such a virtual dental training system, was introduced in 2010. Modern dental training devices using haptic technology from the company MOOG provide an extraordinarily accurate virtual reality simulation of dental treatments [40].

In 2014, the University of Pennsylvania School of Dental Medicine became the first dental school in North America to incorporate this technology into its curriculum. These units are already in use at dental schools around Europe and Asia.

4. Healthy lifestyle promotion with 3D models:- The tremendous visual impact of virtual reality can be used to educate and aware people, especially youth regarding the harmful effects of such bad habits as smoking, alcohol and drug abuse, an unwholesome diet, sedentary lifestyle, and others and the right path of life. Illustrative 3D models can show how the human body gradually changes under the effect of such habits and how long it takes to recover, fully or partially, from the damage. Such visualization presents an intelligible and relatable method of promoting a healthy life and urging people to change their lives before it’s too late [39].

5. Helping patients with Alzheimer’s:- VR tools help manage psychological and behavioural symptoms of the disease such as Alzheimer’s, agitation, aberrant motor behavior, anxiety, and elation. Around the globe today, 50 million individuals are affected with dementia. By the year 2050, this number is projected to be more than triple from its current level andis expected to reach $2 trillion by 2030. Virtual and augmented reality (VR and AR) uses computer-generated environments for diagnosing and treatment of Alzheimer’s disease for relieving its symptoms. VR stimulation provided by the virtual reality tours helped dementia patients tap into old memories and help in faster recovery of lost memory and improve communication between patients and their families or carers. The researchers suggest this may show a correlation between VR and positive mood and motivation to engage in the art class.

6. Feel stay-at-home via VR during long in-hospital treatment:- Virtual reality goggles can assist in relieving any stress brought on by long-term hospitalisation, which is difficult and unpleasant for all patients, especially youngsters who miss their parents and friends. Recently, we can see in the COVID-19 pandemic VR tools such as psychological intervention techniques for good mental health without physical contact. In these situations, medical virtual reality makes it simpler for friends and family to be in constant contact with their hospitalised friends and family members [41].

Drone

A drone is an unmanned aircraft known as unmanned aerial vehicles (UAVs) or an unmanned aircraft system that can be remotely controlled or fly autonomously using software-controlled flight plans in its embedded system integrated with onboard sensors and a global positioning system (GPS) [42]. Navigational systems, such as GPS drones use autopilot functions to travel along a path that is predetermined and sensors for the purpose to detecting obstacles and avoiding collisions, which makes it a more effective system. Drones have proven to be beneficial to various fields such as the agriculture industry, military, public safety, commercial shipping, law enforcement and traffic surveillance, and education. Drones in medicine and healthcare are often used in public health and disaster relief, telemedicine, and medical transport.

They include (1) Prehospital Emergency Care, (2) Expediting Laboratory Diagnostic Testing, and (3) Surveillance.

Prehospital Emergency Care:- Prehospital care is provided by emergency medical services (EMS) responders, who are the initial healthcare providers at the scene of the disaster. Medical drones can be flown to deliver medical supplies such as automated external defibrillators (AED), red blood cells, medicine, or vaccines, to save emergency patients in remote areas.

Transporting Devices and Materials

In the past, it took a lot of time and money to carry medical items to and from patients. Now drones are widely used by providers to send products like hazardous materials and small medical gadgets to the required places in short time span. In addition, touchless communication is made possible by drones, which slows the spread of contagious diseases such as pandemic cases [43]. For this purpose fixed-wing drones are used due to their superior engine efficiency and their ability to cover great distances covering around 400 hectares. Fixed-wing drones resemble airplanes, and fixed-wing hybrids, which incorporate wings and rotors on a single battery. These types of drones are better suited for flying long distances. A proof-of-concept unmanned system was put to test in 2007 by researchers from the National Health Laboratory Service (NHLS) and Denel Dynamics (UAV division) to transport microbiological samples from remote clinics to NHLS centres more effectively for quick Human Immunodeficiency Virus (HIV) testing.

Enable Backup Transport System in the Pandemic

Global health providers are now looking for different ways of transmitting vaccines to rural and remote areas—and drones are helping the cause. Drones allow safe, easy, and efficient access to places that are difficult or dangerous to reach through traditional delivery means. By using drones, providers can ensure that people who need vaccines can obtain them in a timely manner.