Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Edin Cubro"'
Autor:
William Trevena, Xiang Zhong, Amos Lal, Lucrezia Rovati, Edin Cubro, Yue Dong, Phillip Schulte, Ognjen Gajic
Publikováno v:
Frontiers in Physiology, Vol 15 (2024)
IntroductionDigital twins of patients are virtual models that can create a digital patient replica to test clinical interventions in silico without exposing real patients to risk. With the increasing availability of electronic health records and sens
Externí odkaz:
https://doaj.org/article/a3aa2820a214472c8608ee28b4da56b2
Autor:
Lucrezia Rovati, Phillip J. Gary, Edin Cubro, Yue Dong, Oguz Kilickaya, Phillip J. Schulte, Xiang Zhong, Malin Wörster, Diana J. Kelm, Ognjen Gajic, Alexander S. Niven, Amos Lal
Publikováno v:
Frontiers in Medicine, Vol 10 (2024)
BackgroundDigital twins are computerized patient replicas that allow clinical interventions testing in silico to minimize preventable patient harm. Our group has developed a novel application software utilizing a digital twin patient model based on e
Externí odkaz:
https://doaj.org/article/84569bffa7b243b894c5d60d1839bce2
Publikováno v:
IEEE Robotics and Automation Letters. 7:7287-7294
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dd58d0c5fcfc5910b108da9fb4715c86
https://doi.org/10.1109/lra.2022.3183253
https://doi.org/10.1109/lra.2022.3183253
Autor:
Ognjen Gajic, Brian W. Pickering, Sarah Chalmers, Heyi Li, Edin Cubro, Yue Dong, Amos Lal, Kilickaya Oguz, Vitaly Herasevich, Guangxi Li
Publikováno v:
Critical Care Medicine. 49:611-611
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::48107674c4ab3765ab4197f190ec6d7a
https://doi.org/10.1097/01.ccm.0000730744.82258.38
https://doi.org/10.1097/01.ccm.0000730744.82258.38
Autor:
Guangxi Li, Edin Cubro, Sarah Chalmers, Yue Dong, Oguz Kilickaya, Ognjen Gajic, Heyi Li, Vitaly Herasevich, Amos Lal, Brian W. Pickering
Publikováno v:
Critical Care Explorations
Supplemental Digital Content is available in the text.
Objectives: To develop and verify a digital twin model of critically ill patient using the causal artificial intelligence approach to predict the response to specific treatment during the fi
Objectives: To develop and verify a digital twin model of critically ill patient using the causal artificial intelligence approach to predict the response to specific treatment during the fi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b6d4badebb804c906c6230a23c14f4c
https://doi.org/10.1097/cce.0000000000000249
https://doi.org/10.1097/cce.0000000000000249