Machine learning is being pressed into play to extract rich information from imaging and clinical data to aid the non-invasive and accurate diagnosis of multiple liver conditions.

Machine learning is a next generation technology and a sub-set of Artificial Intelligence.

As the use of machine learning algorithms in health care continues to expand, there are growing concerns about equity, fairness, and bias in the ways in which machine learning models are developed ...

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).

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 ...

Machine learning can be applied in various ways in security, for instance, in malware analysis, to make predictions, and for clustering security events. It can also be used to detect previously ...

The team then used this representation as input for other machine learning models that make specific predictions. In their study, the team first trained their autoencoder using ECGs and heart MRIs ...

Key Takeaways ProtGPS predicts protein localization, offering insights into function and disease. The AI model identifies mutations that alter localization, revealing potential disease mechanisms.