Background Artificial intelligence ECG (AI-ECG) models can predict cardiovascular outcomes, but their clinical adoption is limited by restricted access to training data and uncertain generalisability.

Kennesaw State University student Josiah Ware is helping turn CT scans into digital models of the human heart, research that could one day help doctors detect problems faster and personalize treatment ...

This Collection supports and amplifies research related to SDG3, SDG9 and SDG10. Physics-Informed Machine Learning (PI-ML) combines principles from physics- and biology-based modeling with data-driven ...

A tool developed by the American Heart Association (AHA), proven to accurately predict heart disease risk for Americans, can be applied to the global population, a new study led by NYU Langone Health ...

Blood pressure is a key metric of cardiovascular health, but standard methods for measuring it rely on occasional readings ...

EMBL researchers created SDR-seq, a next-generation tool that decodes both DNA and RNA from the same cell. It finally opens access to non-coding regions, where most disease-associated genetic variants ...

A new AI blood test may forecast major cardiovascular disease risks years before clinical onset by reading real-time ...

UC San Diego researchers combined artificial intelligence with molecular biology to unravel how immune cells in the gut decide between inflammation and healing, a process gone awry in Crohn’s disease.

The team built a DenseNet – a densely connected convolutional neural network – that learns hierarchical features directly ...

The 12-lead ECG hasn't changed in a century. The algorithms reading it have. Three CEOs and one educator on whether doctors ...

Scientists are developing a test which could one day be used to predict how a patient’s illness will progress, and even how well they will respond to treatment. The international team, led by ...

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