Medical Dialogues

Machine Learning Enables Personalized Prediction of Glaucoma Progression, Suggests Research

According to the authors, incorporating a broad spectrum of biomarkers allows the models to reflect the continuous and ...
Healio

AI models using OCT data accurately predicted glaucoma progression

The progression of glaucoma was accurately predicted by machine learning models based on structural, functional and vascular ...
WLRN

'95% accuracy': FIU researchers use artificial intelligence to detect heart disease early

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 ...
Morning Overview on MSN

AI is learning to decode diseases hidden in your DNA

Artificial intelligence is rapidly becoming medicine’s most powerful microscope, revealing patterns in human DNA that were ...
News Medical

Using AI models to improve prediction of CKD's progression to end-stage renal disease

Chronic kidney disease (CKD) is a complex condition marked by a gradual decline in kidney function, which can ultimately progress to end-stage renal disease (ESRD). Globally, the prevalence of the CKD ...
Rochester Institute of Technology

RIT researchers use machine learning to better understand the pathways of disease

Cancer, Alzheimer’s, and other diseases follow a pathway in the human body. It starts at the molecular and cellular levels, and through a series of complex interactions can lead to the development and ...
European Medical Journal

Machine Learning Shows Promise in Predicting RA Treatment Response

A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...
Scientific Research Publishing

Early Alzheimer’s Disease Detection from Short Speech Samples Using Lightweight, Interpretable Linguistic Markers ()

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 ...