Machine learning and AI for healthcare : big data for improved health outcomes / Arjun Panesar.
2021
R859.7.A78 P36 2021eb
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Details
Title
Machine learning and AI for healthcare : big data for improved health outcomes / Arjun Panesar.
Author
Panesar, Arjun.
Edition
2nd ed.
ISBN
9781484265376 (electronic bk.)
1484265378 (electronic bk.)
148426536X
9781484265369
1484265378 (electronic bk.)
148426536X
9781484265369
Publication Details
[Place of publication not identified] : Apress, 2021.
Language
English
Description
1 online resource
Item Number
10.1007/978-1-4842-6537-6 doi
Call Number
R859.7.A78 P36 2021eb
Dewey Decimal Classification
610.285/63
Summary
This updated second edition offers a guided tour of machine learning algorithms and architecture design. It provides real-world applications of intelligent systems in healthcare and covers the challenges of managing big data. The book has been updated with the latest research in massive data, machine learning, and AI ethics. It covers new topics in managing the complexities of massive data, and provides examples of complex machine learning models. Updated case studies from global healthcare providers showcase the use of big data and AI in the fight against chronic and novel diseases, including COVID-19. The ethical implications of digital healthcare, analytics, and the future of AI in population health management are explored. You will learn how to create a machine learning model, evaluate its performance, and operationalize its outcomes within your organization. Case studies from leading healthcare providers cover scaling global digital services. Techniques are presented to evaluate the efficacy, suitability, and efficiency of AI machine learning applications through case studies and best practice, including the Internet of Things. You will understand how machine learning can be used to develop health intelligence-with the aim of improving patient health, population health, and facilitating significant care-payer cost savings. You will: Understand key machine learning algorithms and their use and implementation within healthcare Implement machine learning systems, such as speech recognition and enhanced deep learning/AI Manage the complexities of massive data Be familiar with AI and healthcare best practices, feedback loops, and intelligent agents.
Bibliography, etc. Note
Includes bibliographical references and index.
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Access limited to authorized users.
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text file
PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed February 26, 2021).
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ITpro collection
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Machine learning and AI for healthcare.
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Table of Contents
Chapter 1: What Is Artificial Intelligence?
Chapter 2: Data
Chapter 3: What Is Machine Learning
Chapter 4: Machine Learning Algorithms
Chapter 5: How to Perform Machine Learning
Chapter 6: Preparing Data
Chapter 7: Evaluating Machine Learning Models
Chapter 8: Machine Learning and AI Ethics
Chapter 9: The Future of Healthcare
Chapter 10: Case Studies
Appendix A: References
Appendix B: Glossary.-
Chapter 2: Data
Chapter 3: What Is Machine Learning
Chapter 4: Machine Learning Algorithms
Chapter 5: How to Perform Machine Learning
Chapter 6: Preparing Data
Chapter 7: Evaluating Machine Learning Models
Chapter 8: Machine Learning and AI Ethics
Chapter 9: The Future of Healthcare
Chapter 10: Case Studies
Appendix A: References
Appendix B: Glossary.-