Applications of Machine Learning Predictive Models in the Chronic Disease Diagnosis

By Gopi Battineni, Getu Gamo Sagaro, Nalini Chinatalapudi, Francesco Amenta. Journal of Personalized Medicine, 2020

313 citations recorded by the source corpus.

This paper reviews applications of machine learning (ML) predictive models in the diagnosis of chronic diseases. Chronic diseases (CDs) are responsible for a major portion of global health costs. Patients who suffer from these diseases need lifelong treatment. Nowadays, predictive models are frequently applied in the diagnosis and forecasting of these diseases. In this study, we reviewed the state-of-the-art approaches that encompass ML models in the primary diagnosis of CD. This analysis covers 453 papers published between 2015 and 2019, and our document search was conducted from PubMed (Medline), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) libraries. Ultimately, 22 studies were selected to present all modeling methods in a precise way that explains CD diagnosis and usage models of individual pathologies with associated strengths and limitations. Our outcomes suggest that there are no standard methods to determine the best approach in real-time clinical practice since each method has its advantages and disadvantages. Among the methods considered, support vector machines (SVM), logistic regression (LR), clustering were the most commonly used. These models are highly applicable in classification, and diagnosis of CD and are expected to become more important in medical practice in the near future.

Subfields: Artificial Intelligence, Health Informatics, Health Information Management

View Paper: https://www.semanticscholar.org/paper/9b0d0d5adc7d9c72b0a468f6b683f7510984e2e7

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In Artificial Intelligence

1. Yogesh Kumar
2. Ruchika Singla
3. Apeksha Koul
4. Muhammad Fazal Ijaz

In Health Information Management

1. Yogesh Kumar
2. Ruchika Singla
3. Apeksha Koul
4. Muhammad Fazal Ijaz

Citations in the corpus

• Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda (2022, background): “Battineni et al. (2020) reviewed the applications of predictive models of machine learning to diagnose chronic disease.”