Artificial Intelligence and Machine Learning in Public Healthcare - Opportunities and Societal Impact (Paperback, 1st ed. 2021)

This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues. Public health requires special attention as it drives economy and education system. COVID-19 is an example-a truly infectious disease outbreak. The vision of WHO is to create public health services that can deal with abovementioned crucial challenges by focusing on the following elements: health protection, disease prevention and health promotion. For these issues, in the big data analytics era, AI and ML tools/techniques have potential to improve public health (e.g., existing healthcare solutions and wellness services). In other words, they have proved to be valuable tools not only to analyze/diagnose pathology but also to accelerate decision-making procedure especially when we consider resource-constrained regions.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	SpringerBriefs in Computational Intelligence
Release date:	December 2021
First published:	2021
Authors:	K. C. Santosh • Loveleen Gaur
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	74
Edition:	1st ed. 2021
ISBN-13:	978-981-16-6767-1
Categories:	Books > Medicine > General issues > Public health & preventive medicine > General Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	981-16-6767-5
Barcode:	9789811667671

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