Del i serien Explainable AI XAI for Engineering Applications

Smart Distributed Embedded Systems for Healthcare Applications

Häftad, Engelska, 2024

AvPreeti Nagrath,Jafar A. Alzubi,Bhawna Singla,Joel J. P. C. Rodrigues,A. K. Verma

969 kr

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This book discusses the applications and optimization of emerging smart technologies in the field of healthcare. It further explains different modeling scenarios of the latest technologies in the healthcare system and compares the results to better understand the nature and progress of diseases in the human body, which would ultimately lead to early diagnosis and better treatment and cure of diseases with the help of distributed technology. Covers the implementation models using technologies such as artificial intelligence, machine learning, and deep learning with distributed systems for better diagnosis and treatment of diseases. Gives in-depth review of technological advancements like advanced sensing technologies such as plasmonic sensors, usage of RFIDs, and electronic diagnostic tools in the field of healthcare engineering. Discusses possibilities of augmented reality and virtual reality interventions for providing unique solutions in medical science, clinical research, psychology, and neurological disorders. Highlights the future challenges and risks involved in the application of smart technologies such as cloud computing, fog computing, IOT, and distributed computing in healthcare. Confers to utilize the AI and ML and associated aids in healthcare sectors in the post-Covid 19 period to revitalize the medical setup.Contributions included in the book will motivate technological developers and researchers to develop new algorithms and protocols in the healthcare field. It will serve as a vast platform for gaining knowledge regarding healthcare delivery, health- care management, healthcare in governance, and health monitoring approaches using distributed environments. It will serve as an ideal reference text for graduate students and researchers in diverse engineering fields including electrical, electronics and communication, computer, and biomedical fields.

Produktinformation

Utgivningsdatum2024-11-29
Mått156 x 234 x 14 mm
Vikt300 g
FormatHäftad
SpråkEngelska
SerieExplainable AI XAI for Engineering Applications
Antal sidor184
FörlagTaylor & Francis Ltd
ISBN9781032183497

Tillhör följande kategorier

Informationsteknik: allmänt inom Data och IT
Systemvetenskap och AI inom Data och IT
Energiteknik inom Naturvetenskap och teknik
Biomedicinsk teknik inom Medicin

Chapter 1: Healthcare Engineering Using AI and Distributed TechnologiesAshish Kumar, Bennett University, Greater Noida, Uttar Pradesh, IndiaPrince Sareen, Bharati Vidyapeeth’s College of Engineering, New Delhi, IndiaAman Arora, University of Texas, Austin, USA1.1 Introduction: 1.2 Related work1.3 Impact of AI in the healthcare industry 1.4 Transforming healthcare with distributed computing1.5 AI-based Robots in the healthcare ecosystem 1.6 Conclusion and Future ScopeChapter 2: Cloud Computing in Healthcare: A Systematic Study Raunak Negi, Jishnu Bhardwaj, and Preeti NagrathBharati Vidyapeeth’s College of Engineering, New Delhi, India2.1. Introduction2.2. Literature Review2.3. MEDLINE2.4 Monitoring Software for the Cloud2.5 Biomedicine and healthcare benefit from cloud computing2.6 Biotech Solutions in the Cloud2.7. Cloud-based Molecular Simulation Tools2.8 Cloud-based Medical Imaging Solutions2.9. Medical Solutions in the Cloud 2.10. Fog computing and healthcare 2.11. Threats with cloud computing2.12. Future Research 2.13 ConclusionChapter 3: Medical Information Extraction of Clinical Notes and Pictorial Visualization of Electronic Medical Records Summary InterfacePraveen Singh and Gopal ChaudharyBharati Vidyapeeth’s College of Engineering, New Delhi, IndiaJoao Alexandre Lobo MarquesUniversity of Saint Joseph Macau, China3.1 Introduction3.2 Related works3.3 Pictorial Visualization of data3.4 Methodology for information extraction3.5 Results3.6 Conclusion and future workChapter 4: Investigations on RFID Enabled Healthcare Usage and Adoption IssuesPankaj Palta, Rahul Kakkar, Sumeet Goyal, Manvinder SharmaCGC – College of Engineering, Punjab, IndiaJoginder Singh, Chandigarh Group of Colleges, Punjab, India4.1 Abstract4.2 Background 4.3 RFID in Health Care System4.4 RFID Adoption Issues4.5 ConclusionReferencesChapter 5: Photonic crystal fiber plasmonic sensor for applications in medicineMonika Kiroriwal and Poonam SingalDeenbandhu Chhotu Ram University of Science & Technology, Murthal, Haryana, India5.1 Introduction5.2 Background and development of photonic crystal fiber 5.3 Plasmonic sensor based on photonic crystal fiber5.4 Fabrication Techniques5.5 Future applications of plasmonic sensors5.6 ConclusionChapter 6: (Augmented reality as a boon to disability)Ashish KumarBennett University, Greater Noida, Uttar Pradesh, IndiaRaja Bharati Vidyapeeth’s College of Engineering, New Delhi, IndiaMuhammad Fazal ljazSejong University, Seoul, South Korea6.1 Introduction: Aim and real use cases of augmented reality6.2 Related work And Discussion6.3 Technology Advancement Using AR for Empowering Disabled People6.4 AR solutions for teaching specialized students6.5 AR accessible technology to people6.6 ConclusionChapter 7: (Augmented and Virtual Reality: Transforming the Future of Psychological and Medical Sciences)Gurjinder Singh, Anjali Kataria, Shinnu Jangra, Rubina Dutta, Archana MantriChitkara University Institute of Engineering and Technology, Punjab, IndiaJasminder Kaur Sandhu Chandigarh University, Gharuan, Mohali, India.Thennarasan SabapathyUniversiti Malaysia Perlis (UniMAP), Perlis, Malaysia7.1. Introduction7.2 Use of AR Technology in Medical Science7.3 Challenges and Opportunities7.4 ConclusionChapter 8: Artificial Intelligence in Healthcare: Perspectives from Post-Pandemic timesTapash Rudra Amity Institute of Biotechnology, Amity University, Kolkata, IndiaShyam Bihari Goyal City University, Selagor, Malaysia8.2 Introduction8.3 Applications of artificial intelligence (AI) in healthcare before Covid-19 pandemic8.4 An Account of artificial intelligence (AI) guided aids in healthcare: Scenario from post pandemic times8.5 Discussion8.6 ConclusionChapter 9: Bioweapons v/s Computer Based Counter Measure Techniques and Mathematical modeling for prediction of Covid-19Joginder Singh, Gurinderjit Kaur Chandigarh Group of Colleges, Landran, Punjab, IndiaRinkesh Mittal, Sukhdeep Kaur, Kuldeep SharmaChandigarh Engineering College, Landran, Punjab, India9.1 Introduction and history9.2 Genetically Engineered pathogens 9.3 Counter measure by computer based techniques9.4 Mathematical model for COVID-19 Prediction9.5 ConclusionChapter 10: Evolution of Healthcare Sector and Evolving Cyber Attacks – A SummaryJai Ganesh Sekar, Arun Chokkalingam, Dhivya KesavanRMK College of Engineering and Technology, Tami Nadu, India10.1 Healthcare industry and its revolution:10.2 Role of Distributed System in Health Care10.3 Why Healthcare is the biggest target for cyber attackers?10.4 Cyber-attacks in healthcare industries - an infographic10.5 Most frequent attacks in health industries and remedial measures10.6 Research trends in cybersecurity for the health care sector10.7 Conclusion – Defending Healthcare sector from CyberattacksChapter 11: Improving Cardiovascular Health by Deep learningShiva Tushir,Panipat Institute of Engineering and Technology, Samalkha, Panipat, India11.1 Introduction11.2. Machine Learning11.3 Next Generation Machine Learning11.4 Applications of Artificial Intelligence for Cardiovascular Health11.5 Future Scope11.6 Challenges 11.7 Conclusion