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<p>Artificial Intelligence (AI) has triggered a significant change in all areas of research. Especially, AI in healthcare has brought a revolution in Disease prediction and diagnosis. Yet the precision and effectiveness of AI in healthcare are questioned, as even a small error may result in the loss of human life. The access to huge sets of patient data in various forms, such as Electronic Health Records (EHR) and Medical Images, certainly fuels AI technologies to work wonders in achieving precise results. Yet the customisation and creation of AI models with intricate and subtle medical details to suit the healthcare application is the need of the hour.&#xa0;This review article aims to unravel the role of Mathematics behind AI models, particularly in literature related to Disease prediction and diagnosis. It also sheds light on the creation of AI models as they are mathematically modelled and their potential to achieve the desired results, useful to Medical Practitioners and patients. In other words, the article aims to disclose the rationale behind the discovery of novel and accurate AI models in the prediction and diagnosis of Cardiovascular Diseases, Neurological Diseases, Cancer, and Leprosy.&#xa0;From the survey conducted, it is inferred that there is scope for building tailored AI models for prediction and diagnosis of a specific disease in healthcare applications in the phases such as Optimisation and Hyper-parameter Tuning. New avenues of research in the healthcare domain can be explored to propose novel AI models by applying sound Mathematical principles instead of reusing the existing well-established models.</p>

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A survey on mathematics behind AI models for disease prediction and diagnosis in healthcare

  • 期刊论文

  • 发表日期：

    2025年12月4日

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  • Ebenezar Mythatha,
  • S. Jenicka

摘要

Artificial Intelligence (AI) has triggered a significant change in all areas of research. Especially, AI in healthcare has brought a revolution in Disease prediction and diagnosis. Yet the precision and effectiveness of AI in healthcare are questioned, as even a small error may result in the loss of human life. The access to huge sets of patient data in various forms, such as Electronic Health Records (EHR) and Medical Images, certainly fuels AI technologies to work wonders in achieving precise results. Yet the customisation and creation of AI models with intricate and subtle medical details to suit the healthcare application is the need of the hour. This review article aims to unravel the role of Mathematics behind AI models, particularly in literature related to Disease prediction and diagnosis. It also sheds light on the creation of AI models as they are mathematically modelled and their potential to achieve the desired results, useful to Medical Practitioners and patients. In other words, the article aims to disclose the rationale behind the discovery of novel and accurate AI models in the prediction and diagnosis of Cardiovascular Diseases, Neurological Diseases, Cancer, and Leprosy. From the survey conducted, it is inferred that there is scope for building tailored AI models for prediction and diagnosis of a specific disease in healthcare applications in the phases such as Optimisation and Hyper-parameter Tuning. New avenues of research in the healthcare domain can be explored to propose novel AI models by applying sound Mathematical principles instead of reusing the existing well-established models.