A machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and numerous recognized categorization methods.

Using the machine learning models, the scientists could establish that among the metrics evaluated, EKG was the most efficient in detecting cardiovascular disease in both men and women.

More information: Yu Xu, Machine learning optimized polygenic scores for blood cell traits stratify sex-specific trajectories and identify genetic correlations with disease, Cell Genomics (2022 ...

Cardiovascular disease is the leading cause of death not only in the United States but globally, per the World Health ...

Explainable machine learning aggregates polygenic risk scores and electronic health records for Alzheimer’s disease prediction. Scientific Reports , 2023; 13 (1) DOI: 10.1038/s41598-023-27551-1 ...

An analysis on 1,194 patients with NSCLC was performed to evaluate the prognostic signatures of quantitative imaging features, extracted with deep learning. 27 In our work, we trained machine learning ...

Study aims to develop a machine learning model to predict cardiovascular disease using indicators of oral infections Mar 17, 2023 ECG-based AI model can predict undiagnosed structural heart disease ...

The researchers found many cases in which a disease-associated mutation appeared to change a protein’s localization. They tested twenty examples in cells, using fluorescence to compare where in the ...