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Machine Learning in Medicine: Enhancing Diagnosis, Treatment, and Healthcare Delivery

Machine Learning in Medicine: Enhancing Diagnosis, Treatment, and Healthcare Delivery
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Author(s): Pooja Dehankar (Ajeenkya D.Y. Patil School of Engineering, India)and Susanta Das (Ajeenkya D.Y. Patil University, India)
Copyright: 2025
Pages: 30
Source title: Exploration of Transformative Technologies in Healthcare 6.0
Source Author(s)/Editor(s): Piyush Kumar (IILM University, Gurugram, India), Pankaj Rahi (Institute of Health Management and Research, Bangalore, India), S.D. Gupta (Institute of Health Management and Research, Bangalore, India), Kirti Udayai (Max Healthcare Institute Limited, India)and Prashant Singh (Independent Researcher, India)
DOI: 10.4018/979-8-3693-7210-4.ch006

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Abstract

ML is a game-changing technology for improving diagnosis, customizing therapy, & streamlining healthcare delivery because of its capacity to handle & learn from enormous volumes of data. ML-based big data analysis has many benefits for assimilating & assessing vast volumes of intricate health care data. Early diagnosis & monitoring of drug-related safety issues were facilitated by ML algorithms that discovered hidden correlations between medications, medical products, & adverse events. This chapter highlights the benefits of ML in Medicine. To achieve the best possible results, it will be essential to improve clinical decision support, sickness diagnosis, & individualized treatment techniques. The chapter discusses important issues to keep in mind when applying ML in the medical field, e.g., data privacy, model interpretability, bias reduction, & regulatory compliance. Lastly it discusses the future of ML in medicine. Through responsible & ethical adoption of new technology, medical community can provide more individualized, efficient, & effective care to improve patient outcomes.

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