TMCnet

FDA Grants De Novo Classification to neuropacs™, a First-in-Class AI-Based MRI Diagnostic Aid for Parkinsonian Syndromes

Neuropacs™ Corp., an innovator in AI-enabled neurological imaging, today announced that the U.S. Food and Drug Administration has granted De Novo classification to neuropacs™, a diffusion MRI-based ...
Business Insider

Esperion’s Bempedoic Acid Receives Multiple Class 1 Recommendations in 2026 ACC/AHA Multisociety Guideline for Management of Dyslipidemia

– Bempedoic Acid Receives Strongest Endorsement from AHA/ACC Multisociety Guideline for Patients with Statin Intolerance and in Primary and Secondary Prevention Patients with Severe ...
GitHub

ECG Arrhythmia Classification using MIT-BIH Dataset

This project implements an end-to-end deep learning pipeline for automated heartbeat classification using the MIT-BIH Arrhythmia Dataset. The system performs ECG signal preprocessing, heartbeat ...
Frontiers

Advancing standardized cattle behavior classification with a random forest model evaluated across diverse datasets

The lack of precise, autonomous tools for monitoring and classifying cattle behavior limits farmers’ ability to make proactive and informed decisions regarding grazing and herd management. Currently, ...
IEEE

Dual-View Alignment Learning With Hierarchical-Prompt for Class-Imbalance Multi-Label Image Classification

Abstract: Real-world datasets often exhibit class imbalance across multiple categories, manifesting as long-tailed distributions and few-shot scenarios. This is especially challenging in ...
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 ...
IEEE

MC-NCLWO: Newton’s Cooling Law-Based Oversampling Algorithm for Multi-class Imbalanced Datasets with Feature Noise

Abstract: Imbalanced data classification remains a fundamental challenge in machine learning, especially in multi-class scenarios where feature noise, class overlap, and small disjunct sub-concepts ...