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 ...
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 ...
Early-stage rehabilitation is crucial for the functional recovery of patients with proximal femur fractures. Predicting functional prognosis at such an early stage can simplify the process of planning ...
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 ...
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 ...
Enhancing Readability of Lay Abstracts and Summaries for Urologic Oncology Literature Using Generative Artificial Intelligence: BRIDGE-AI 6 Randomized Controlled Trial We trained and tested ML systems ...
6don MSN
Even weak ocean models can provide valuable information for environmental forecasts, study shows
Oxygen depletion in the western Baltic Sea is not uncommon. Oxygen-poor conditions regularly occur in deeper waters, placing ...
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 ...
Two complementary predictors (DAAE-M and ELIE) estimate individualized 5-year progression risk using routine clinical data, extending the prior DAAE framework beyond static baseline risk. Registry ...
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 ...
illustrating the comprehensive zero-shot benchmark of 19 universal machine learning interatomic potentials and the dominant impact of training data composition for surface energy prediction. A ...
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