2 Minute Medicine

Deep-learning models displayed expert-level accuracy in detecting epileptiform discharges on electroencephalogram (EEG) recordings

Li and colleagues developed a deep-learning model to analyze EEG recordings and detect event-level EEG spikes. 2. The model achieved high accuracy and a low false-positive rate, with only 32% of human ...

Press Advantage Examines How AI Systems Classify Press Releases as High-Signal Content for Search Processing

Las Vegas, NV - February 05, 2026 - PRESSADVANTAGE - Press Advantage, a leading press release distribution service, has ...
EurekAlert!

Label attention meets deep learning: a novel model for ICD-11 automatic classification of Chinese EMRs

Electronic medical records (EMRs) enable healthcare institutions to digitally document patients’ clinical conditions, treatment processes, and diagnostic outcomes, supporting paperless clinical ...
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

The acquisition sites include: CALTECH, California Institute of Technology; CMU, Carnegie Mellon University; KKI, Kennedy Krieger Institute; LEUVEN, University of Leuven; MAX, Ludwig Maximilians ...
C&EN

Bridging Deep Learning and In Situ Spectroelectrochemistry: A Hybrid Framework for Uncovering Fundamental Insights of Multi-Electron Processes

Energy and Environment Science & Technology, Idaho National Laboratory, Idaho Falls, Idaho 83415, United States ...
IEEE

Multi-label Chest X-ray Image Classification via Category Disentangled Causal Learning

Abstract: Chest X-rays (CXR) are widely used to diagnose chest diseases. Since patients often suffer from multiple diseases simultaneously, it is crucial to identify multiple abnormalities in a single ...