AI and Machine Learning Paradigms for Health Monitoring System
Intelligent Data Analytics
(Sprache: Englisch)
This book embodies principles and applications of advanced soft computing approaches in engineering, healthcare and allied domains directed toward the researchers aspiring to learn and apply intelligent data analytics techniques. The first part covers AI,...
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Klappentext zu „AI and Machine Learning Paradigms for Health Monitoring System “
This book embodies principles and applications of advanced soft computing approaches in engineering, healthcare and allied domains directed toward the researchers aspiring to learn and apply intelligent data analytics techniques. The first part covers AI, machine learning and data analytics tools and techniques and their applications to the class of several hospital and health real-life problems. In the later part, the applications of AI, ML and data analytics shall be covered over the wide variety of applications in hospital, health, engineering and/or applied sciences such as the clinical services, medical image analysis, management support, quality analysis, bioinformatics, device analysis and operations. The book presents knowledge of experts in the form of chapters with the objective to introduce the theme of intelligent data analytics and discusses associated theoretical applications. At last, it presents simulation codes for the problems included in the book for better understanding for beginners.
Inhaltsverzeichnis zu „AI and Machine Learning Paradigms for Health Monitoring System “
Optimization Solutions for Demand Side Management and Monitoring.- An Insight into Tool and Software Used in AI, Machine Learning and Data Analytics.- Security Enhancement and Monitoring for Data Sensing Networks Using a Novel Asymmetric Mirror-Key Data Encryption Method.- Introduction to Cuckoo Search and its Paradigms: A Bibliographic Survey and Recommendations.- Routing Protocols for Internet of Vehicles: A Review.- Introduction to Particle Swarm Optimization and its Paradigms: A Bibliographic Survey.- Classification and Monitoring of Injuries Around Knee Using Radiographs Based Deep Learning Algorithm.- Artificial Intelligence: It's Role in Diagnosis and Monitoring against COVID-19.- Predicting Future, past and Misinterpreted COVID-19 Cases using Bidirectional LSTM Model for Proper Health Monitoring: Advances in Data Analytics.- Data Driven Analysis to Identify the Role of Relational Benefit in Developing Customer Loyalty and Management: A Case Study.
Autoren-Porträt
Dr. Hasmat Malik (M'16) received Diploma in Electrical Engineering from Aryabhatt Govt. Polytechnic Delhi, B.Tech. degree in electrical & electronics engineering from the GGSIP University, Delhi, M.Tech degree in electrical engineering from National Institute of Technology (NIT) Hamirpur, Himachal Pradesh, and Ph.D in power system from Electrical Engineering Department, Indian Institute of Technology (IIT) Delhi, India. He is currently a Postdoctoral Scholar at BEARS, University Town, NUS Campus, Singapore. He is a chartered Engineer [IEI]. He is a Life Member of Institute of Engineers (India) (IEI), Indian Society for Technical Education (ISTE), Institution of Electronics and Telecommunication Engineering (IETE), International Association of Engineers (IAENG), Hong Kong, International Society for Research and Development, London (ISRD) and Member of the Institute of Electrical and Electronics Engineers (IEEE), USA and Mir Labs, Asia. He has published more than 100 researcharticles, including papers in international journals, conferences and book chapters. He is a Guest Editor of Special Issue of Journal of Intelligent & Fuzzy Systems, 2018, 2020 (SCI, Impact Factor 2020:1.851), (IOS Press). He received the POSOCO Power System Award (PPSA-2017) for his Ph.D work for research and innovation in the area of power system. He has received best research papers awards at IEEE INDICON-2015, and full registration fee award at IEEE SSD-2012 (Germany). He has supervised 23 PG students. He is involved in several large R&D projects. His principal area of research interests is artificial intelligence, machine learning and big-data analytics for renewable energy, smart building & automation, condition monitoring and online fault detection & diagnosis (FDD). Dr Nuzhat Fatema has 10 years of experience in intelligent data analytics using AI & Machine learning for hospital and health care management. Dr. Fatema is the Co-founder of the
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Intelligent Prognostic Private Limited. Dr Fatema speaks nationally and internationally about the importance and power of data in hospital and healthcare systems.Dr. Fatema a BAMS graduated from Maharashtra University of Health Sciences, India. She has cured many patients with her skills of medicinal knowledge. Later to go beyond the clinical skills, she has achieved post-graduation in hospital management from International Institute of Health Management Research (IIHMR), Delhi. This was the platform where she has utilized her clinical skills with her managerial skills using artificial intelligence (AI), Machine Learning (ML) and Data Analytics. She has worked as a research associate at National Board of Examinations (NBE) India and dealt with the accreditation process for post graduate courses in different multi-specialty hospitals in the country. She has authored one book describing a trouble free tool prepared by using different standardized manuals of medicines in different countries for usage of the most complicated drug like Warfarin. She has published several research papers in renowned international journals and conferences. Presently she is associated with Singapore Polyclinic, Singapore.Her area of interest is AI, ML and intelligent data analytics application in healthcare, monitoring, prediction, forecasting, detection & diagnosis where she believes that it's a data driven world with stockpile of database in the industry which is to be used to extract value to make better informed, more accurate decisions in diagnosis, management and better outcomes in industry care. Simply throwing the numbers by analyzing any data has zero value; therefore she has produced narratives using data for decision making. She has been doing research study by spotting patterns in data and setting up infrastructure in the real-time industrial monitoring domain.
Jafar A. Alzubi is Associate Professor atA
Jafar A. Alzubi is Associate Professor atA
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Bibliographische Angaben
- 2022, 1st ed. 2021, XXIV, 513 Seiten, 183 farbige Abbildungen, Masse: 17,2 x 23,4 cm, Kartoniert (TB), Englisch
- Herausgegeben: Hasmat Malik, Nuzhat Fatema, Jafar A. Alzubi
- Verlag: Springer, Berlin
- ISBN-10: 9813344148
- ISBN-13: 9789813344143
Sprache:
Englisch
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