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RIT students make finals—and history—as part of autonomous race at Indianapolis Speedway

RIT students make finals—and history—as part of autonomous race at Indianapolis Speedway
rit.edu - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from rit.edu Daily Mail and Mail on Sunday newspapers.

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Students make finals—and history—as part of autonomous race at Indianapolis Speedway

Students make finals—and history—as part of autonomous race at Indianapolis Speedway
rit.edu - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from rit.edu Daily Mail and Mail on Sunday newspapers.

New York , United States , Ho Chi Minh City , H Chíinh , Republic Of , Rochester Institute Of Technology , Watkins Glen International , South Korea , Reggio Emilia , Emilia Romagna , Technische Universit , Prem Bharatia , Andrew Keats , Andrew Saba , Charlie King , Nayana Suvarna , Van Pham , University Of Pisa , University Of Waterloo Canada , Purdue University , United States Military Academy At West Point , University Of Alabama , Auburn University , University Of Waterloo , University Of California San Diego , Technology South Korea ,

AI Program Quickly Predicts Which Patients with COVID-19 Might have Lethal Complications

AI Program Quickly Predicts Which Patients with COVID-19 Might have Lethal Complications
Written by AZoRoboticsMay 13 2021
A new study has found that a computer program trained to observe patterns by examining thousands of chest X-rays estimated, with up to 80% precision, which patients with coronavirus disease (COVID-19) would develop fatal complications within 4 days.
Chest X-ray from patient severely ill from COVID-19, showing (in white patches) infected tissue spread across the lungs. Image Credit: Courtesy of Nature Publishing or npj Digital Medicine.
The program developed by scientists at NYU Grossman School of Medicine made use of several hundred gigabytes of data gleaned from 5,224 chest X-rays obtained from 2,943 severely ill patients infected with SARS-CoV-2, the virus responsible for the infections. ....

Nan Wu , Yindalon Aphinyanaphongs , Aakash Kaku , Stanislaw Jastrzebski , Ben Zhang , Narjes Sharif Razavian , Yvonnew Lui , Carlos Fernandez Granda , Krzysztofj Geras , David Kudlowitz , Farah Shamout , Lea Azour , Siddhant Dogra , Williamh Moore , Yiqiu Artie Shen , Department Of Radiology , Grossman School Of Medicine , Study Co , National Institutes Of Health , York University , National Science Foundation , Nature Publishing , Digital Medicine , Study Co Lead Investigator , Assistant Professor , Computer Engineering ,

Artificial intelligence tool uses chest X-ray to differentiate worst cases of COVID-19

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Chest X-ray from patient severely ill from COVID-19, showing (in white patches) infected tissue spread across the lungs
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Credit: CREDIT
Courtesy of Nature Publishing or npj Digital Medicine
Trained to see patterns by analyzing thousands of chest X-rays, a computer program predicted with up to 80 percent accuracy which COVID-19 patients would develop life-threatening complications within four days, a new study finds.
Developed by researchers at NYU Grossman School of Medicine, the program used several hundred gigabytes of data gleaned from 5,224 chest X-rays taken from 2,943 seriously ill patients infected with SARS-CoV-2, the virus behind the infections. ....

Nan Wu , Ben Zhang , Krzysztof Geras , Yvonne Lui , Abu Dhabi , Carlos Fernandez Granda , David Kudlowitz , William Moore , Farah Shamout , Yindalon Aphinyanaphongs , Aakash Kaku , Stanislaw Jastrzebski , Lea Azour , Narges Razavian , Yiqiu Artie Shen , Siddhant Dogra , Grossman School Of Medicine , Department Of Radiology , National Institutes Of Health , Data Science Center , York University , National Science Foundation , Digital Medicine , New York University , National Institutes , Jungkyu Park ,