Using AI to identify at-risk patient groups in emergency room triage systems

A multinational collaboration at Eitri medical innovation center in Bergen, Norway, has used machine learning models to identify patient groups at risk of being mistreated.
The Manila Times

MicroCloud Hologram Inc. Releases Hybrid Quantum-Classical Convolutional Neural Network, Achieving New Breakthrough in MNIST Multi-Class Classification

MicroCloud Hologram Inc. (NASDAQ: HOLO), ('HOLO” or the 'Company'), a technology service provider, proposed a Quantum Convolutional Neural Network (QCNN) based on hybrid quantum-classical learning and ...
Devdiscourse

Explainable AI model achieves breakthrough accuracy in ovarian cancer detection

The researchers argue that the integration of explainable AI into clinical decision-making pipelines could reshape cancer ...
Phys.org

Between rain and snow, machine learning finds nine precipitation types

In research that could improve weather forecasting and winter driving safety, a University of Michigan-led study distinguished nine distinct precipitation types—varieties of rain, snow and mixed-phase ...
Morningstar

insitro Partners with Lilly to Build First-in-Kind Machine Learning Models to Advance Small Molecule Drug Discovery

insitro, a pioneer in machine learning for drug discovery and development, today announced a new collaboration with Eli Lilly and Company (Lilly) to develop advanced machine learning models that can ...
The American Journal of Managed Care

Novel Machine Learning Model Improves MASLD Detection in Type 2 Diabetes

A machine learning–driven web tool based on 13 standard patient metrics demonstrates strong predictive performance for MASLD, ...