Artificial Intelligence and Machine Learning in Public Healthcare

Opportunities and Societal Impact
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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.

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ReiheSpringerBriefs in Applied Sciences and Technology
ISBN 9789811667671
Ausgabe 1st ed. 2021
Erscheinungsdatum 27.11.2021
Umfang 74 Seiten
Genre Technik/Allgemeines, Lexika
Format Taschenbuch
Verlag Springer Singapore
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