Leveraging Green AI and Big Data Informatics for Personalized Disease Prediction in Clinical Decision Making

Author:

Yadav Mohit1ORCID,Singh Priyank Kumar2ORCID,Gochhait Saikat3ORCID,Gaur Nisha4ORCID,Wijethilaka Puwakpitiyage Gayan Dhanushka5

Affiliation:

1. O.P. Jindal Global University, India

2. Doon University, Dehradun, India

3. Symbiosis Institute of Digital and Telecom Management, Symbiosis International (Deemed), Pune, India & Samara State Medical University, Russia

4. Gautam Buddha University, India

5. Sri Lanka Institute of Marketing, Sri Lanka

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.

Publisher

IGI Global

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