Researchers have developed a new "emotionally aware" AI-based model for classifying mental health conditions, which could ...
It is a common misperception that electrocardiograms (ECGs) simply contain data about heart activity. However, modern ECGs ...
Abstract: Electrocardiogram (ECG) is an authoritative source to diagnose and counter critical cardiovascular syndromes such as arrhythmia and myocardial infarction (MI). Current machine learning ...
A new study published in Engineering has combined machine learning (ML) and experimental validation to identify dihydromyricetin (DHM), a natural flavonoid, as a potent inhibitor of the TGF-β/ALK5 ...
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 ...
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 ...
Artificial intelligence programs can spot patterns in electrocardiograms that humans miss. Now, one program is going to be ...
The integration of AI and Machine Learning into injury prediction is transforming how researchers, clinicians, and sports ...
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 ...
BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
aInstitute for Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, Zurich, Switzerland bDepartment of Nuclear Medicine, University Hospital Zurich and ...