Ultra‑robust machine‑learning models run stable molecular simulations at extreme temperatures

Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular ...
University of Surrey

Data-efficient and transferable machine learning-based predictive models for catastrophic risk assessment in offshore wind infrastructure

This industry-collaborative PhD project offers the opportunity to work at the intersection of machine learning, structural engineering and renewable energy to develop innovative and impactful ...
Que.com on MSN

The next frontier of machine learning: 2026 breakthroughs and the rise of world models

The Next Frontier of Machine Learning: 2026 Breakthroughs and the Rise of World Models The landscape of artificial intelligence and ...
News-Medical.Net

Machine learning model can predict 28-day mortality in sepsis patients

Sepsis is one of the most common and lethal syndromes encountered in intensive care units (ICUs), and acute respiratory ...
Clinical Pain Advisor

Machine Learning Model May Predict Pain-Related QOL After Endometriosis Surgery

Machine learning model predicts poor pain-related quality of life after endometriosis surgery to assist clinicians with preoperative counseling.
Frontiers

From Meta-omics to Mechanisms: Interpretable AI for Microbial Ecology

Microbial ecology is rapidly evolving with the integration of artificial intelligence (AI) and machine learning into the study of complex microbial ...
Medscape

Can a Machine Learning Model Predict Liver Cancer?

Using routine clinical data, the model gauges liver cancer risk better than existing tools, offering a potential way to identify high-risk patients missed by current screening criteria.
CMSWire

When Predictive Analytics Misleads CX Strategy

Correlation can look convincing in dashboards. Without causal analysis, organizations risk optimizing for the wrong signals.

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 ...