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Study shows reliable model to predict licensure exam outcome

A study conducted by experts from the University of the Philippines-Diliman showed that logistic regression is a reliable ...
Oncology Nurse Advisor

Machine Learning Model Predicts Nutritional Risk in Nasopharyngeal Carcinoma

Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.
Medical Dialogues

Interpretive models could help predict risk of preoperative DVT in elderly patients with hip fracture: Study

A new study published in the International Journal of General Medicine showed that physicians may reliably estimate the ...
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 ...
InfoQ

Meta Details GEM Ads Model Using LLM-Scale Training, Hybrid Parallelism, and Knowledge Transfer

Meta released details about its Generative Ads Model (GEM), a foundation model designed to improve ads recommendation across ...
Scientific Research Publishing

Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity ()

Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...
BMJ Open

Using virtual twin-based AI models to detect atrial fibrillation and improve stroke outcomes [TAILOR]: a multicentre prospective cohort study

Introduction Atrial fibrillation (AF) is the leading cause of cardioembolic stroke and is associated with increased stroke severity and fatality. Early identification of AF is essential for adequate ...