Yadav, Mohit, Singh, Priyank Kumar, Gochhait, Saikat, Gaur, Nisha and Wijethilaka, Puwakpitiyage Gayan Dhanushka (2024) Leveraging green AI and big data informatics for personalized disease prediction in clinical decision making. In: Green AI-powered intelligent systems for disease prognosis. IGI Global Publishing, pp. 91-112. ISBN 9798369312438
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Abstract
This chapter explores the potential of green AI and big data informatics for personalized disease prediction in clinical decision making. Green AI prioritizes efficiency, minimizing computational resources needed to analyze vast healthcare datasets. Big data informatics provides the platform to manage and analyze these datasets for knowledge discovery. This chapter delves into how green AI algorithms optimize resource utilization while big data platforms leverage diverse patient data for more accurate, individual risk assessments. The applications in clinical decision-making encompass early detection, risk stratification, and personalized treatment plans. However, ethical considerations regarding data privacy, bias, and potential job displacement require careful attention. Finally, the future directions highlight advancements in green AI efficiency, explainable models, and integration with other health technologies, paving the way for a future of proactive healthcare and patient empowerment.
Item Type: | Book Section |
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Subjects: | Physical, Life and Health Sciences > Medicine Social Sciences and humanities > Social Sciences > Social Sciences (General) Social Sciences and humanities > Social Sciences > Health (Social sciences) |
JGU School/Centre: | Jindal Global Business School |
Depositing User: | Subhajit Bhattacharjee |
Date Deposited: | 27 Aug 2024 11:39 |
Last Modified: | 07 Nov 2024 14:42 |
Official URL: | https://doi.org/10.4018/979-8-3693-1243-8.ch006 |
URI: | https://pure.jgu.edu.in/id/eprint/8350 |
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