Machine Learning and Analytics in Healthcare Systems

This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine. It will combine the design and problem-solving skills of engineering with health sciences, in order to advance healthcare treatment. The book will include areas such as diagnosis, monitoring, and therapy. The book will provide real-world case studies, gives a detailed exploration of applications in healthcare systems, offers multiple perspectives on a variety of disciplines, while also letting the reader know how to avoid some of the consequences of old methods with data sharing. The book can be used as a reference for practitioners, researchers and for students at basic and intermediary levels in Computer Science, Electronics and Communications.

Himani Bansal has over 14 years of wide experience in Academics and IT industry. She is currently working as Assistant Professor in Jaypee Institute of Information Technology, Noida, India and possess many reputed certifications such as UGC National Eligibility Test (NET), IBM Certified Academic Associate DB2 9 Database and Application Fundamentals, Google Analytics Platform Principles by Google Analytics Academy, E-Commerce Analytics by Google Analytics Academy and RSA (Rational Seed Academy) and SAP-ERP professional. Her general research interests include Machine learning and Data Analytics, Cloud Computing, Business Analytics, Data Mining and Information Retrieval. She has filed 4 patents and has around 40 publications including edited books, authored book, international journals and conferences of high repute. She has served as section editor, guest editor, convener and session chair for various upright Journals and Conferences such as SCPE, NGCT, IndiaCom, CSI Digital Life, IJAIP, JGIM, ICACCI, ICCCA, etc. and has reviewed many research papers. She serves as Life Member of various professional societies such as CSI, ISTE, CSTA and IAENG and is an active member of IEEE and ACM. Recently, IEEE has conferred her with Senior Membership. Balamurugan Balusamy has served up to the position of Associate Professor in his stint of 14 years of experience with VIT University, Vellore. He has completed his Bachelors, Masters and Ph.D. Degrees from Top premier institutions .His passion is teaching and adapts different design thinking principles while delivering his lectures .He has done around 30 books on various technologies and visited 15 plus countries for his technical discourse .He has several top notch conferences in his resume and has published over 150 of quality journal, conference and book chapters combined. He serves in the advisory committee for several startup and forums and does consultancy work for industry on Industrial IOT. He has given over 175 talks in various events and symposium. He is currently working as professor in Galgotias University and teaches students, does research on Block chain and IOT. T. Poongodi is working as an Associate Professor in School of Computing Science and Engineering, Galgotias University, Greater Noida, India. She has completed Ph.D in Information Technology (Information and Communication Engineering) from Anna University, Tamil Nadu, India. Her main thrust research areas are Big Data, Internet of Things, Ad-hoc networks, Network Security and Cloud computing. She is a pioneer researcher in the areas of Bigdata, Wireless network, Internet of Things and has published more than 25 papers in various international journals. She has presented paper in National/International Conferences, published book chapters in CRC Press, IGI global, Springer, Elsevier and edited books in CRC, IET, Wiley, Springer and Apple Academic Press. Firoz Khan KP was born in Kerala, India, in 1974. He received his BSc degree in Electronics from the Bharatiyaar University, Coimbatore, India, in 1991 and Masters Degree in information Technology from University of Southern Queensland, Australia, and another Master's Degree in Information Network and Computer Security (with Honors) from New York Institute of Technology, Abu Dhabi, UAE, in 2006 and 2016 respectively. He is currently working towards his PhD in Computer Science from the British University in Dubai, Dubai, UAE. In 2001, he joined the Higher Colleges of Technology in Computer Information Science department as a Teaching Technician and continued on to become a Faculty member in 2005. He is currently holding the position of a Lecturer, with security and networking being his primary areas of teaching. His current research fields include computer security, machine learning, deep learning and computer networking.

Chapter 1 Data Analytics in Healthcare Systems - Principles, Challenges, and Applications Chapter 2 Systematic View and Impact of Machine Learning in Healthcare Systems Chapter 3 Foundation of Machine Learning-Based Data Classification Techniques for Health Care Chapter 4 Deep Learning for Computer-Aided Medical Diagnosis Chapter 5 Machine Learning Classifiers in Health Care Chapter 6 Machine Learning Approaches for Analysis in Healthcare Informatics Chapter 7 Prediction of Epidemic Disease Outbreaks, Using Machine Learning Chapter 8 Machine Learning-Based Case Studies for Healthcare Analytics: Electronic Health Records, Smart Health Monitoring, Disease Prediction, Precision Medicine, and Clinical Support Systems Chapter 9 Applications of Computational Methods and Modeling in Drug Delivery Chapter 10 Healthcare Data Analytics Using Business Intelligence Tool Chapter 11 Machine Learning-Based Data Classification Techniques in Healthcare Using Massive Online Analysis Framework Chapter 12 Prediction of Coronavirus (COVID-19) Disease Health Monitoring with Clinical Support System and its Objectives Index

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