COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...

The progression of glaucoma was accurately predicted by machine learning models based on structural, functional and vascular biomarkers, including those from OCT angiography, according to data ...

A highly accurate AI model improves prediabetes prediction by integrating antioxidant status with standard risk factors.

FIU Researchers are training AI to detect heart conditions, like aortic stenosis and heart failure, by analyzing heart sound data to improve early diagnosis and risk prediction. The future of heart ...

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic lateral sclerosis, or ALS, earlier from a blood sample, a study suggests.

Doctors may soon be able to diagnose an elusive form of heart disease within seconds by using an AI model developed at ...

Alzheimer’s disease touches millions of families across the United States and remains the most common neurodegenerative ...

Investigations suggest V2P may be efficiently applied for the automated identification of causal variants in simulated and actual patient sequencing data across phenotypes.

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...