Prognostic models in healthcare : AI and statistical approaches / Tanzila Saba, Amjad Rehman, Sudipta Roy, editors.
Saba, Tanzila, editor.; Rehman, Amjad, editor.; Roy, Sudipta, editor.
2022
RC78.7.D35
Available Online

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Title Prognostic models in healthcare : AI and statistical approaches / Tanzila Saba, Amjad Rehman, Sudipta Roy, editors.
ISBN 9789811920578 (electronic bk.)
9811920575 (electronic bk.)
9789811920561
9811920567
DOI https://doi.org/10.1007/978-981-19-2057-8
Published Singapore : Springer, [2022]
Copyright ©2022
Language English
Description 1 online resource : illustrations (chiefly color).
Item Number 10.1007/978-981-19-2057-8 doi
Call Number RC78.7.D35
Dewey Decimal Classification 616.07/50285
Summary This book focuses on contemporary technologies and research in computational intelligence that has reached the practical level and is now accessible in preclinical and clinical settings. This book's principal objective is to thoroughly understand significant technological breakthroughs and research results in predictive modeling in healthcare imaging and data analysis. Machine learning and deep learning could be used to fully automate the diagnosis and prognosis of patients in medical fields. The healthcare industry's emphasis has evolved from a clinical-centric to a patient-centric model. However, it is still facing several technical, computational, and ethical challenges. Big data analytics in health care is becoming a revolution in technical as well as societal well-being viewpoints. Moreover, in this age of big data, there is increased access to massive amounts of regularly gathered data from the healthcare industry that has necessitated the development of predictive models and automated solutions for the early identification of critical and chronic illnesses. The book contains high-quality, original work that will assist readers in realizing novel applications and contexts for deep learning architectures and algorithms, making it an indispensable reference guide for academic researchers, professionals, industrial software engineers, and innovative model developers in healthcare industry.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed July 13, 2022).
Added Author Saba, Tanzila, editor.
Rehman, Amjad, editor.
Roy, Sudipta, editor.
Series Studies in big data ; v. 109.
Available in Other Form Print version: 9789811920561
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