Background Machine learning based on clinical characteristics has the potential to predict coronary CT angiography (CCTA) findings and help guide resource utilisation.Methods From the SCOT-HEART ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

Two new studies from the Department of Computational Biomedicine at Cedars-Sinai are advancing what we know about using machine learning and big data to improve health care and medical research. Both ...

View all available purchase options and get full access to this article. Cardiovascular Performance Program Study Group: The authors acknowledge the contributions of the Cardiovascular Performance ...

This project applies Haar wavelet transform for ECG signal denoising and trains CNN/SVM classifiers to detect cardiac arrhythmias. Built using the MIT-BIH dataset, it's designed for research, learning ...

The model is trained solely on ECG signals using HRV and EDR features with an LSTM-based neural network.

This study explores the development of two predictive models for the yield sooting index (YSI) of various fuels using the advanced capabilities of machine learning (ML), particularly multilayer ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

Isomerase has announced the launch of EvoSelect®, a machine learning-guided enzyme engineering platform designed to accelerate development timelines, enhance performance under industrial conditions, ...