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AI Tool Uses CT Scans to Predict Decreased Blood Flow to the Heart

Researchers and colleagues at Cedars-Sinai have created an artificial intelligence (AI) tool that employs computed tomography (CT) scans to detect patients who are at risk of decreased blood flow to the heart. ....

Andrew Lin , Eyal Klein , Alex Smith , Tyler Olson Shutterstock , Nipun Manral , Keiichiro Kuronuma , Daniels Berman , Kajetan Grodecki , Yuka Otaki , Donghee Han , Richard Rios , Evangelos Tzolos , Piotrj Slomka , Damini Dey , Priscilla Mcelhinney , Alan Kwan , Sinai Biomedical Imaging Research Institute , Quantitative Image Analysis Lab At Cedars , Professor Of Biomedical Sciences , Sheldong Adelson Medical Research Foundation , Blood Institute , National Heart , Image Credit , Study Corresponding Author , Biomedical Sciences , Quantitative Image Analysis Lab ,

AI tool uses CT scans to identify patients at risk of reduced blood flow to the heart

Cedars-Sinai investigators and colleagues have developed an artificial intelligence (AI) tool that uses computed tomography (CT) scans to identify patients at risk of reduced blood flow to the heart. ....

Kajetan Grodecki , Andrew Lin , Donghee Han , Eyal Klein , Yuka Otaki , Richard Rios , Emily Henderson , Evangelos Tzolos , Nipun Manral , Keiichiro Kuronuma , Damini Dey , Piotrj Slomka , Priscilla Mcelhinney , Alan Kwan , Daniels Berman , Biomedical Imaging Research Institute , Sheldong Adelson Medical Research Foundation , Blood Institute , Biomedical Sciences , National Heart , Benjamin Shou , Sebastien Cadet , Medical Research , Artificial Intelligence , Chest Pain , Computed Tomography ,

Deep Learning with SPECT Accurately Predicts Major Adverse Cardiac Events

Deep Learning with SPECT Accurately Predicts Major Adverse Cardiac Events
itnonline.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from itnonline.com Daily Mail and Mail on Sunday newspapers.

New York , United States , Tel Aviv , Columbia University , Yale University , Sacred Heart Medical Center , Beer Sheba , Tejas Parekh , Joanna Liang , Piotr Slomka , Los Angeles , Robert Miller , Andrew Einstein , Serge Van Kriekinge , Sharmila Dorbala , Yuka Otaki , Timothy Bateman , Wei Chih Chun , Edward Miller , Ananya Singh , Albert Sinusas , Damini Dey , Daniel Berman , Philipp Kaufmann , Paul Kavanagh , Department Of Radiology ,

Deep Learning with SPECT Accurately Predicts Major Adverse Cardiac Events

Deep Learning with SPECT Accurately Predicts Major Adverse Cardiac Events
miragenews.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from miragenews.com Daily Mail and Mail on Sunday newspapers.

New York , United States , Tel Aviv , Columbia University , Yale University , Sacred Heart Medical Center , Beer Sheba , Tejas Parekh , Joanna Liang , Piotr Slomka , Los Angeles , Robert Miller , Andrew Einstein , Serge Van Kriekinge , Sharmila Dorbala , Yuka Otaki , Timothy Bateman , Wei Chih Chun , Edward Miller , Ananya Singh , Albert Sinusas , Damini Dey , Daniel Berman , Philipp Kaufmann , Paul Kavanagh , Department Of Radiology ,

Deep learning with SPECT accurately predicts major adverse cardiac events

An advanced artificial intelligence technique known as deep learning can predict major adverse cardiac events more accurately than current standard imaging protocols, according to research presented at the Society of Nuclear Medicine and Molecular Imaging 2021 Annual Meeting. Utilizing data from a registry of more than 20,000 patients, researchers developed a novel deep learning network that has the potential to provide patients with an individualized prediction of their annualized risk for adverse events. ....

New York , United States , Tel Aviv , Columbia University , Yale University , Sacred Heart Medical Center , Beer Sheba , Tejas Parekh , Joanna Liang , Piotr Slomka , Los Angeles , Robert Miller , Andrew Einstein , Serge Van Kriekinge , Sharmila Dorbala , Yuka Otaki , Timothy Bateman , Wei Chih Chun , Edward Miller , Ananya Singh , Albert Sinusas , Damini Dey , Daniel Berman , Philipp Kaufmann , Paul Kavanagh , Department Of Radiology ,