Researchers develop new 'emotionally aware' model for classifying mental health conditions

Researchers have developed a new "emotionally aware" AI-based model for classifying mental health conditions, which could ...

ECG privacy model shields age, sex and race while preserving heart risk signals

It is a common misperception that electrocardiograms (ECGs) simply contain data about heart activity. However, modern ECGs ...
IEEE

ECG Heartbeat Classification Using Multimodal Fusion

Abstract: Electrocardiogram (ECG) is an authoritative source to diagnose and counter critical cardiovascular syndromes such as arrhythmia and myocardial infarction (MI). Current machine learning ...
IEEE

Inter-Patient ECG Classification Using Deep Convolutional Neural Networks

Abstract: In this paper we present fully automatic interpatient electrocardiogram (ECG) signal classification method using deep convolutional neural networks (CNN). ECG is simple and non-invasive way ...
Frontiers

Advancements in Smart Diagnostics for Understanding Neurological Behaviors and Biosensing Applications

The intersection of machine learning, biosensing technologies, and neurological behavior analysis presents fertile ground for groundbreaking research and innovation. This research topic aims to bridge ...
Knowridge

AI could detect early heart disease in ECGs with 94% accuracy

Artificial intelligence is already changing the way people search for information, translate languages, and communicate. Now, researchers believe the same technology could also help doctors detect ...

Doctors Thought It Was Asthma. A.I. Flagged a Serious Heart Problem.

Artificial intelligence programs can spot patterns in electrocardiograms that humans miss. Now, one program is going to be ...
Frontiers

AI & Machine Learning for Injury Prediction: From Data to Preventive Strategies

The integration of AI and Machine Learning into injury prediction is transforming how researchers, clinicians, and sports ...
Nature

Gut microbiome signatures discriminate deep vein thrombosis through machine learning and metabolic analysis

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...
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 ...
The Lancet

FDA-cleared artificial intelligence and machine learning-based medical devices and their 510(k) predicate networks

aInstitute for Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, Zurich, Switzerland bDepartment of Nuclear Medicine, University Hospital Zurich and ...