Volume 7 • Issue 2 • PP: 07–17 • 2024
Advancements and Future Directions in Machine Learning for Medical Diagnostics: A Comprehensive Review
Open Access & Copyright
© 2024 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
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Machine learning (ML)-based techniques are increasingly used to address problems in fields such as finance, marketing, production, the environment, health care, and security. ML can identify patterns, interpret data, reveal hidden relationships, and analyze large datasets, potentially improving the specificity, sensitivity, predictability, and stability of diagnostic systems. This review examines the application of machine learning in medicine and its use in diagnostics, including medical chemistry, wearable sensors, cancer, brain health, and medical imaging. It discusses application-specific model adaptations and offers findings and references to guide academics, practitioners, decision-makers, and future research.
Keywords
References
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