Heat may be 10 billion times more efficient for randomization ...

University of Virginia School of Data Science researcher Heman Shakeri has been awarded a major new research grant to lead work at the intersection of machine learning and diabetes care.

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...

An AI-powered model that analyzes electrocardiograms was able to accurately detect COPD early in internal testing and ...

Artificial intelligence is becoming a useful tool across a wide array of sectors. Therefore, it is little surprise that AI ...

Dr Michele Orini shares how machine learning can help identify critical VT ablation targets for a safer, data-driven ...

Discover how AI is revolutionizing veterinary radiology, and learn how algorithms support specialists for faster, more ...

Background: This study developed a machine learning model to predict postoperative heart failure (HF) risk in non-cardiac surgery patients. Methods: Using data from 489 patients (109 HF cases, 380 ...

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for millions of deaths each year according to the World Health Organization (WHO). Early detection of these diseases ...

Heart disease is a prevalent and life-threatening condition that requires accurate and timely diagnosis. This project focuses on developing and evaluating machine learning models to classify ...

Abstract: Predicting the onset of cardiovascular disease at an early stage using machine learning algorithms is the primary goal of this research. Improved model performance, reduced overfitting, ...