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Artificial intelligence can predict risk of new-onset atrial fibrillation and AF-related stroke

Researchers find AI can predict new atrial fibrillation, stroke risk

 E-Mail DANVILLE, Pa. - A team of scientists from Geisinger and Tempus have found that artificial intelligence can predict risk of new atrial fibrillation (AF) and AF-related stroke. Atrial fibrillation is the most common cardiac arrhythmia and is associated with numerous health risks, including stroke and death. The study, published in Circulation, used electrical signals from the heart measured from a 12-lead electrocardiogram (ECG) to identify patients who are likely to develop AF, including those at risk for AF-related stroke. Each year, over 300 million ECGs are performed in the U.S. to identify cardiac abnormalities within an episode of care. However, these tests cannot generally detect future potential for negative events like atrial fibrillation or stroke, said Joel Dudley, chief scientific officer at Tempus. This critical work stems from our major investments in cardiology to generate algorithms that make existing cardiology tests, such as ECGs, smarter and capab

Genomic Data Commons provides unprecedented cancer data resource

 E-Mail The National Cancer Institute s Genomic Data Commons (GDC), launched in 2016 by then-Vice President Joseph Biden and hosted at the University of Chicago, has become one of the largest and most widely used resources in cancer genomics, with more than 3.3 petabytes of data from more than 65 projects and over 84,000 anonymized patient cases, serving more than 50,000 unique users each month. In new papers published Feb. 22 in Nature Genetics, the UChicago-based research team shares new details about the GDC, which is funded by the National Cancer Institute (NCI), via subcontract with the Frederick National Laboratory for Cancer Research, currently operated by Leidos Biomedical Research, Inc. One of the papers describes the design and operation of the GDC. The other describes the pipelines used by the GDC for the harmonization of data submitted to the GDC and the generation of datasets used by the GDC research community.

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