A deep learning tool developed by researchers from MIT and Harvard Medical School shows promise in predicting heart failure ...

Through an AI tool ... be used for heart failure prediction,” Dhingra said. The working model is currently hosted on the CarDS lab website, where people can freely use it for research purposes.

"It has the potential to set new standards for cardiovascular disease prevention and management, as well as advance the forefront of using AI to analyze images for transformational health care." The ...

Researchers at Case Western Reserve University, University Hospitals, and Houston Methodist are embarking on a groundbreaking initiative to harness artificial intelligence (AI) for predicting heart ...

Photographs taken of the retina at the back of the eye can give an indication of brain health, and by using AI software to analyse the information, scientists may be able to spot signs of disease ...

Bournemouth University is one of the partners on ARTEMIs, a four-year research project funded by the European Union’s Horizon programme. The project will explore how ‘virtual twins’ – digital ...

AI-enabled ECG biological age (ECG-BA) improves disease risk classification beyond chronological age, enhancing early ...

We recently compiled a list of the 9 AI Stocks Investors Are Monitoring. In this article, we are going to take a look at ...

Researchers have developed a method that leverages artificial intelligence to ensure accurate heart scans without added radiation or cost.

and helps guide providers in preventing heart disease. Using well-established coronary computed tomography angiography (CCTA) combined with artificial intelligence (AI) software, expert ...

To address this, CVD prevention plans rely on prediction models like atherosclerotic cardiovascular disease (ASCVD) risk scores to estimate the risk of heart disease. However, previous studies ...

To create a "digital cell map" that can be used throughout the entire process of identifying disease ... heart of incurable diseases like Alzheimer's, and unraveling them is a highly challenging task.