Description

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Recently medical informatics, especially health informatics, has received various applications from machine learning and IoT. The applications of machine learning and IoT technology have entirely changed the predictive capability of the concerned disease. The input data to the machine learning and IoT-based devices are sometimes not structured; they could be unstructured as well; therefore, analyzing such unstructured data has significance. These data could be image related such as X-Ray images, ECG images, and others. Therefore, this edited book will focus on structure and unstructured data applications.

Sickness and health-related data collection are also significant benefits of health analytics. Finally, further progress in the patients' health is made, and decisions are taken on further treatments based on the data. The Internet of Things (IoT) has emerged as a preferred solution to many emerging problems in the last few years. This colligated ecosystem in electronic devices can be worn as accessories and embedded in clothing. Also, the IoT-related apps have helped the data collection process and contributed to information technology. The interesting fact is that IoT applications can be found more in the healthcare system, especially healthcare informatics. IoT-powered applications in healthcare immensely benefit patients and physicians, hospitals, and overall healthcare systems. The wearables devices that are enabled with machine learning and IoT are changing the form of wearables like fitness bands, measuring blood pressure, and checking heart rate monitoring and glucometer concepts.

IoT and machine learning-enabled health care systems can change the treatment's efficiency and quality on the treatment front. It can monitor in real-time about the conditions of the patients, and with the use of app-based smartphones, the dynamics of the treatments are changing forever. Therefore, the delivery model of the integrated services of health care using IoT and machine learning will completely change the treatment of heart diseases, kidney disease, hypertension, and other diseases. The care model for patients will be completely different. This edited book will address the problems mentioned above and shall provide solutions. Each chapter shall address a unique machine and IoT-enabled application for health-related problems.

The key features of this edited book are:

1. Application related to the amalgamations of machine learning and IoT for medical data

2. Explores the disease diagnosis incorporation powered by IoT and enabled with predictive models

3. Recent advancements in machine learning and deep learning models in health analytics.

4. Digs into cost reduction, treatment improvement, quick disease diagnosis, and drug and equipment management of healthcare using IoT systems.

5. Presents several case studies related to machine learning, deep learning, and IoT applications toward health analytics.

About the Author

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Pijush Samui is working as a professor in the civil engineering department at NIT Patna, India. He graduated in 2000, with a B.Tech. in Civil Engineering from Indian Institute of Engineering Science and Technology, Shibpur, India. He received his M.Sc. in Geotechnical Earthquake Engineering from Indian Institute of Science, Bangalore, India (2004). He holds a Ph.D. in Geotechnical Earthquake Engineering (2008) from Indian Institute of Science, Bangalore, India. He was a postdoctoral fellow at University of Pittsburgh (USA) (2008-2009) and Tampere University of Technology (Finland) (2009- 2010). In 2010, Dr. Pijush joined the Center for Disaster Mitigation and Management at VIT University as an Associate Professor. He was promoted to full Professor in 2012. Dr. Pijush is the recipient of the prestigious CIMO fellowship (2009) from Finland, for his integrated research on the design of railway embankment. He was awarded Shamsher Prakash Research Award (2011) by IIT Roorkee for his innovative research on the application of Artificial Intelligence in designing civil engineering structures. He was selected as the recipient of IGS Sardar Resham Singh Memorial Award - 2013 for his innovative research on infrastructure project. He was elected Fellow of the International Congress of Disaster Management in 2010. He served as a guest editor in disaster advance journal. He also serves as an editorial board member in several international journals. He has been selected as an adjunct professor at Ton Duc Thang University (Ho Chi Minh City, Vietnam). He has been visiting professor at Far East Federal University (Russia).Dr. Sanjiban Sekhar Roy is a Professor in the School of Computer Science and Engineering, Vellore Institute of Technology. His research interests include deep learning, advanced machine learning & Generative-AI. He has published around 74 articles in reputed international journals (with SCI impact factors), conferences and editorial board members to a handful of international journals and reviewer to many highly reputed journals. Dr. Roy also has edited around 10 books with reputed international publishers. Besides, the Ministry of National Education, Romania & "Aurel Vlaicu" University, Romania has awarded Dr. Roy with "Diploma of Excellence" for the scientific research activity in 2019. Dr Sanjiban was also an Associate Researcher with Ton Duc Thang University, Vietnam, from 2019 to 2020.Dr. Wengang ZHANG is currently full professor in School of Civil Engineering, Chongqing University, China. His research interests focus on Underground Engineering, Slope Engineering, Bio-inspired Geotechnics, as well as big data and machine learning in geotechnics and geoengineering. He is now the members of the ISSMGE TC304 (Reliability), TC309 (Machine Learning), TC219 (System Performance of Geotechnical Structures) and TC222 (Digital Twin). He also serves Geoscience Frontiers as Associate Editor, Editorial member for Georisk, Journal of Rock Mechanics and Geotechnical Engineering as well as Underground Space Dr Zhang has been selected as 2021 Highly cited Chinese Scholars and the World's Top 2% Scientists for years 2019 and 2020. He won the 2019 Computers and Geotechnics Sloan Outstanding Paper Award and 2021 Underground Space Outstanding Paper Award. Y-H. Taguchi received a B.S. degree in physics from the Tokyo Institute of Technology and a Ph.D. degree in physics from the Tokyo Institute of Technology. He is currently a full professor with the Department of Physics, Chuo University, Japan. His works have been published in leading journals such as Physical Review Letters, Bioinformatics, and Scientific Reports. His research interests include bioinformatics, machine-learning, and non-linear physics. He is also an editorial board member of Frontiers in Genetics: RNA, PloS ONE, PloS Complex Systems, BMC Medical Genomics, Medicine (Lippincott Williams & Wilkins journal), BMC Research Notes, non-coding RNA (MDPI), Scientific Reports, and IPSJ Transaction on Bioinformatics and was also recognized as top 2% scientist of the world in 3rd consecutive years (2021, 2022, 2023) according to analysis of Stanford University, USA and report of Elsevier in bioinformatics.