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.
TMCnet

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

Data Encoding Stage: The MNIST dataset contains grayscale handwritten digit images. Each image is scaled and normalized, then mapped to eight qubits through Angle Encoding or Amplitude Encding. This ...
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 ...
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, ...