Healthcare Solutions Using Machine Learning and Informatics

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Synopsis
Healthcare Solutions Using Machine Learning and Informatics covers novel and innovative solutions for healthcare that apply machine learning and biomedical informatics technology. The healthcare sector is one of the most critical in society. This book presents a series of artificial intelligence, machine learning, and intelligent IoT-based solutions for medical image analysis, medical big-data processing, and disease predictions. Machine learning and artificial intelligence use cases in healthcare presented in the book give researchers, practitioners, and students a wide range of practical examples of cross-domain convergence. The wide variety of topics covered include: Artificial Intelligence in healthcare Machine learning solutions for such disease as diabetes, arthritis, cardiovascular disease, and COVID-19 Big data analytics solutions for healthcare data processing Reliable biomedical applications using AI models Intelligent IoT in healthcare The book explains fundamental concepts as well as the advanced use cases, illustrating how to apply emerging technologies such as machine learning, AI models, and data informatics into practice to tackle challenges in the field of healthcare with real-world scenarios. Chapters contributed by noted academicians and professionals examine various solutions, frameworks, applications, case studies, and best practices in the healthcare domain.
Copyright:
2023

Book Details

Book Quality:
Publisher Quality
Book Size:
254 Pages
ISBN-13:
9781000767209
Related ISBNs:
9781032345222, 9781003322597, 9781032201986
Publisher:
CRC Press
Date of Addition:
Copyrighted By:
selection and editorial matter, Punit Gupta, Dr. Dinesh Kumar Saini, and Rohit Verma individual chapters, the contributors.
Adult content:
No
Language:
English
Has Image Descriptions:
No
Categories:
Nonfiction, Medicine
Submitted By:
Bookshare Staff
Usage Restrictions:
This is a copyrighted book.
Edited by:
Punit Gupta
Edited by:
Dinesh Kumar Saini
Edited by:
Rohit Verma

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