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Can lend chapters, not whole ebooks
Title
Artificial intelligence and machine learning in healthcare / Ankur Saxena, Shivani Chandra.
ISBN
9789811608117 (electronic bk.)
9811608113 (electronic bk.)
9811608105
9789811608100
Publication Details
Singapore : Springer, 2021.
Language
English
Description
1 online resource
Item Number
10.1007/978-981-16-0811-7 doi
Call Number
R859.7.A78
Dewey Decimal Classification
610.285/63
Summary
This book reviews the application of artificial intelligence and machine learning in healthcare. It discusses integrating the principles of computer science, life science, and statistics incorporated into statistical models using existing data, discovering patterns in data to extract the information, and predicting the changes and diseases based on this data and models. The initial chapters of the book cover the practical applications of artificial intelligence for disease prognosis & management. Further, the role of artificial intelligence and machine learning is discussed with reference to specific diseases like diabetes mellitus, cancer, mycobacterium tuberculosis, and Covid-19. The chapters provide working examples on how different types of healthcare data can be used to develop models and predict diseases using machine learning and artificial intelligence. The book also touches upon precision medicine, personalized medicine, and transfer learning, with the real examples. Further, it also discusses the use of machine learning and artificial intelligence for visualization, prediction, detection, and diagnosis of Covid -19. This book is a valuable source of information for programmers, healthcare professionals, and researchers interested in understanding the applications of artificial intelligence and machine learning in healthcare.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed May 14, 2021).
Available in Other Form
Print version: 9789811608100
Chapter 1_Big Data Analytics and AI for Healthcare
Chapter 2_Genetics with Big Data and AI
Chapter 3_AI and Big Data for next-generation sequencing
Chapter 4_Artificial Intelligence for Computational Biology
Chapter 5_Artificial intelligence and machine learning in clinical development
Chapter 6_Big data analytics for personalized medicine
Chapter 7_Generating and Managing Healthcare data with AI
Chapter 8_Big Data and Artificial Intelligence for diseases
Chapter 9_Artificial Intelligence and Big Data for Public Health
Chapter 10_Biasness in Healthcare Big Data and Computational Algorithms
Chapter 11_AI and ML in Healthcare: An Ethical perspective.
