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HeartBeam partners with Mount Sinai to advance AI-powered ECG technology

HeartBeam (NASDAQ:BEAT) announced a strategic collaboration with the Icahn School of Medicine at Mount Sinai aimed at accelerating the development and clinical validation of next-generation artificial ...

Machine learning finds four behavior symptom profiles tied to early dementia processes

Behavioral changes—such as anxiety, depression, irritability, apathy or agitation, collectively known as neuropsychiatric ...
The Lancet

When to and when not to use machine learning in risk prediction models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...
Medical Xpress

AI model detects prediabetes using ECG data without need for blood tests

DiaCardia, a novel artificial intelligence model that can accurately identify individuals with prediabetes using either 12-lead or single-lead electrocardiogram (ECG) data, has been developed. This ...
ahajournals.org

Abstract 4368538: Fusion Machine Learning Architectures for Improving ECG classification of acute coronary events

Introduction: Acute coronary syndrome (ACS) is a life-threatening emergency, with occlusion myocardial infarction (OMI) requiring rapid diagnosis and treatment. The 12-lead ECG remains the primary ...
IEEE

ECGNet: High-Precision ECG Classification Using Deep Learning and Advanced Activation Functions

Abstract: The electrocardiogram (ECG) is an important tool in diagnosing heart diseases. In this study, we introduce ECGNet a customized deep learning model that utilizes advanced activation functions ...
The New York Times

The Professors Are Using ChatGPT, and Some Students Aren’t Happy About It

Students call it hypocritical. A senior at Northeastern University demanded her tuition back. But instructors say generative A.I. tools make them better at their jobs. By Kashmir Hill In February, ...
C&EN

Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.