This review provides a thorough and organized overview of machine learning (ML) applications in predicting heart disease, covering technological advancements, challenges, and future prospects. As ...

Objectives Alzheimer’s disease (AD) poses a significant challenge for individuals aged 65 and older, being the most prevalent form of dementia. Although existing AD risk prediction tools demonstrate ...

We employed the seven machine learning classifiers the model offers to diagnose Parkinson’s disease using significant speech data. Among these ML models, the proposed model achieved an accuracy of ...

Researchers developed COMET, a deep learning framework that leverages electronic health records and omics data to improve predictive modeling and uncover biological insights.

A recent review explored how integrating machine learning with traditional statistical models can enhance disease risk prediction accuracy, a key tool in clinical decision-making.

By integrating multi-omics data, MILTON improves disease prediction and biomarker identification, advancing the field of preventative medicine and diagnostics.

The Disease Prediction Using Machine Learning project is an innovative web application developed with Streamlit. It harnesses advanced machine learning techniques and algorithms to accurately predict ...

Disease Prediction using Machine Learning. Contribute to FinaMunzi/Capstone-4-Disease-Prediction-ML development by creating an account on GitHub.