Machine Learning and Iot Applications for Health Informatics

1. Auflage 2024
ISBN: 978-1-032-54450-2
Verlag: CRC Press

Buch, Englisch, 250 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 531 g

This book brings together leading experts from around the world to explore the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) in healthcare. It provides a platform for studying a future where healthcare becomes more precise, personalized, and accessible for all. The book covers recent advancements that will shape the future of healthcare and how artificial intelligence is revolutionizing disease detection, from analyzing chest X-rays for pneumonia to solving the secrets of our genes. It investigates the transformative potential of smart devices, real-time analysis of heart data, and personalized treatment plan creation. It shows how ML and IoT work and presents real-world examples of how they are leading to earlier and more accurate diagnoses and personalized treatments.

Therefore, this edited book will be an invaluable resource for researchers, healthcare professionals, data scientists, or simply someone passionate about the future of healthcare. Readers will discover the exciting possibilities that lie ahead at the crossroads of ML, IoT, and health informatics.

Zielgruppe

Academic, Postgraduate, and Professional Reference

Autoren/Hrsg.

Samui, Pijush

Sekhar Roy, Sanjiban

Zhang, Wengang

Taguchi, Y H

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke
• Naturwissenschaften Biowissenschaften Biowissenschaften
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein

Inhaltsverzeichnis

Preface. Machine Learning and the Role of IoT in Health Informatics. Bioconductor Packages to Perform Tensor Decomposition Based Unsupervised Feature Extraction. Smart Health: Advancements in Machine Learning and the Internet of Things Solutions. A Study Aimed at Presenting Methodologies for Enhancing Cost Efficiency in Healthcare Systems Based on Internet of Things (IoT)by Incorporating Sophisticated Deep Learning and Artificial Intelligence Techniques. Transforming Healthcare through Machine Learning and the Internet of Things. IoT-powered AI for Precise Pneumonia Detection in Chest X-Rays. Tensor Decomposition in Genomics. IoT, Artificial Intelligence and Cyber Security: The ParadigmsFraming the Future of Digital Healthcare. Integrating IoT, Analytics and Deep Learning in ECG for Cardiovascular care. Transfer Learning for Multiclass Classification of Bone Marrow Cells. Machine Learning, Deep Learning and IoT in Smart Healthcare for Retinal Diseases Management. Index.

Über Autor(innen)

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.