A machine learning model may enable liver cancer risk prediction with routine clinical information

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...
Frontiers

Causal Machine Learning for Treatment Selection and Outcome Optimization in Mood Disorders

Mood disorders represent a major global burden and are characterized by substantial heterogeneity in symptom profiles, treatment response, and clinical ...

Apple trained an AI that captions images better than models ten times its size

Apple researchers have developed a new way to train AI models for image captioning that delivers accurate descriptions while ...

Global Artificial Intelligence (AI) In Precision Medicine Market To Attain USD 10.32 Billion By 2032, Witnessing A CAGR Of 31.35%, Says Markntel Advisors

In Precision Medicine Market To Attain USD 10.32 Billion By 2032, Witnessing A CAGR Of 31.35%, Says Markntel Advisors. NEW DELHI, March 25, 2026 /PRNewswire/ -- According to the in-depth study ...

Turning CO₂ into methanol: Multilayer machine learning speeds up search for better catalysts

Finding high-performing catalysts, which are used to accelerate processes from chemical manufacturing to energy production, ...
Scientific Research Publishing

H-UQ-MFF: Hybrid Uncertainty-Aware Multi-Feature Fusion for Clinically-Translatable Glaucoma Detection with FDA-Compliant Validation ()

Although artificial intelligence (AI) has demonstrated potential in automating glaucoma screening, there is still a significant obstacle in transferring research datasets to actual clinical settings.
European Medical Journal

Transforming Ulcerative Colitis Care: AI-Powered Endoscopic Scoring from Clinical Trials to Clinical Practice

Ulcerative colitis (UC) is a chronic, immune-mediated inflammatory disorder of the colon that follows a relapsing-remitting course. Characterised by mucosal inflammation, the disease requires accurate ...
Scientific Research Publishing

A Lightweight Self-Supervised Representation Learning Framework for Depression Risk Profiling from Synthetic Daily Behavioural Trajectories ()

Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often suffer from ...
ascopubs.org

Automated Tumor International Classification of Diseases Coding of Real-World Pathology Reports Using Self-Hosted Large Language Models

We analyzed 21,364 pathology reports from 10,823 patients documented between 2013 and 2025 at a large German hospital. Five LLMs were evaluated: Llama-3.3-70B-Instruct, DeepSeek-R1-Distill-Llama (8B ...
IEEE

Hierarchy-Aware and Knowledge-Guided Learning for Multi-Label Classification of Retinal Diseases from Fundus Images

Abstract: Retinal diseases (RD) are major causes of global vision impairment. Automated diagnosis using fundus images has significant clinical value, particularly in multi-label classification of RD.
Associated Press

Did anybody do the reading? Colleges grapple with a generational shift in learning — plus AI

Copyright 2026 The Associated Press. All Rights Reserved. Copyright 2026 The Associated Press. All Rights Reserved. Assistant Professor Dr. Hillary Lazar poses for a ...