The purpose of this study was to develop a machine learning-based model using quantitative color fundus photography (CFP) data to predict myopia risk in school-age children, based on the axial ...
Despite significant advances in molecular microbiology, our understanding of the biology of microorganisms, particularly of prokaryotes, remains incomplete due to the pronounced imbalance between the ...
A subscription technology platform with over 100,000 users was losing customers each month despite having access to ...
A machine learning (ML)-based model may aid in-hospital community-acquired pneumonia (CAP) mortality prediction, according to study findings published in Respiratory Medicine. Res ...
Effect of incorporating symptom burden with mortality as a composite outcome on accuracy and bias in palliative care identification algorithms in oncology. This is an ASCO Meeting Abstract from the ...
A new study reveals how AI analyzes routine retinal eye photos to predict Alzheimer’s lifestyle and biological risk factors decades early.
A new study shows that machine-learning models can accurately predict daily crop transpiration using direct plant measurements and environmental data. By training models on seven years of ...
A machine learning study of 4,776 women found AI can predict physical, emotional, and social outcomes after breast cancer ...
A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a complication that can occur late in pregnancy. Preeclampsia is a sudden ...
Study of Over Three Million Patients for Risk of Type 2 Diabetes Demonstrates Potential for More Advanced Approach to Early Identification ...
A recent study published in npj Materials Degradation introduces a two-stage machine learning (ML) framework that predicts the degradation of protective coatings under various environmental conditions ...
Crypto markets generate more usable data than almost any other financial sector. Prices move at all hours, blockchain activity is visible as ...