Medscape

Advanced Machine Learning Model Predicts Onset of Epilepsy and Depression

A large study applies advanced machine learning to identify shared risk factors and predictors of disease onset in patients with epilepsy and depression.

FDA approves first-ever AI tool to detect hidden heart conditions before symptoms show

EchoNext examines the electrical signals captured during a routine ECG. Although these signals may appear normal to the human ...

AI analysis of data from multiple sensors can improve earthquake detection

One seismometer is often not enough to reliably detect earthquakes or human activity such as underground nuclear tests.

AI/ML Innovations Inc. Announces Grant of U.S. Patent Expanding Protection for AI-Driven ECG Analysis

Patent covers machine learning techniques for ECG denoising, rhythm classification, sample-level labelling, wearable cardiac ...
The Lancet

Risk-stratified classification of pulmonary nodule malignancy via a machine learning model integrating imaging and cell-free DNA: a model development and validation study ...

aDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
IEEE

Interpretable Deep Learning Framework for Real-Time ECG Classification and Diagnosis

Abstract: Automatic arrhythmia detection requires effective and clear models because cardiovascular disease is increasingly common. Convolutional neural networks (CNNs) have proven to be the most ...
IEEE

Machine Learning Framework for Industrial Machine Sound Classification in Predictive Maintenance

Abstract: Predictive maintenance, utilising anomalous sound classification, demonstrates a strong potential to identify mechanical faults in industrial machinery. This research proposes a machine ...