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Explorative study on potential of machine learning and artificial intelligence for improved healthcare diagnosis and treatment

Prakash Date, Varsha Pimprale, Sakshi Mandke

Abstract


Machine learning (ML) and Artificial intelligence (AI) have demonstrated substantial promise for enhancing healthcare diagnostics and therapy. This study compares the benefits, drawbacks, and uses of these tools to examine their potential in healthcare. ML systems can find trends, increase diagnosis precision, and support professional judgment. Their efficacy may be constrained, though, by bad data quality, a lack of interpretability, and execution issues. On the other hand, AI can support clinical judgment, enhance patient results, and boost healthcare productivity. However, difficulties in implementing them can arise due to restricted generalizability, data protection issues, and legal conformance. To ensure the effective application and acceptance of these technologies in healthcare, it is essential to understand these benefits and constraints. Healthcare providers of the future will be able to make wiser choices regarding patient assessment and therapy options using AL and ML, resulting in an overall enhancement of healthcare services.


Keywords


AI; diagnosis; health; healthcare industry; ML

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References


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DOI: https://doi.org/10.32629/jai.v7i3.1084

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Copyright (c) 2023 Prakash Date, Varsha Pimprale, Sakshi Mandke

License URL: https://creativecommons.org/licenses/by-nc/4.0/