Zobrazeno 1 - 10
of 23
pro vyhledávání: '"John R. Zech"'
Publikováno v:
BMJ Open, Vol 11, Iss 8 (2021)
Objective To validate an existing clinical decision support tool to risk-stratify patients with acute kidney injury (AKI) for hydronephrosis and compare the risk stratification framework with nephrology consultant recommendations.Setting Cross-sectio
Externí odkaz:
https://doaj.org/article/01f9369f3bf1401999d44fe614e43d9b
Publikováno v:
American Journal of Roentgenology. 219:869-878
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::89575213422407f58f61ef2cb0779770
https://doi.org/10.2214/ajr.22.27873
https://doi.org/10.2214/ajr.22.27873
Autor:
John R Zech, Marcus A Badgeley, Manway Liu, Anthony B Costa, Joseph J Titano, Eric Karl Oermann
Publikováno v:
PLoS Medicine, Vol 15, Iss 11, p e1002683 (2018)
BACKGROUND:There is interest in using convolutional neural networks (CNNs) to analyze medical imaging to provide computer-aided diagnosis (CAD). Recent work has suggested that image classification CNNs may not generalize to new data as well as previo
Externí odkaz:
https://doaj.org/article/86bad117ffd645d7bd86f36b7db6dd6f
Autor:
John R. Zech
Publikováno v:
Radiol Artif Intell
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ac72ed9b49b3b17d5c3450277e727148
https://europepmc.org/articles/PMC9344203/
https://europepmc.org/articles/PMC9344203/
Publikováno v:
Skeletal radiology. 51(8)
Many children who undergo MR of the knee to evaluate traumatic injury may not undergo a separate dedicated evaluation of their skeletal maturity, and we wished to investigate how accurately skeletal maturity could be automatically inferred from knee
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b46e3585f05e95e24157dc6d2d397e1b
https://pubmed.ncbi.nlm.nih.gov/35184211
https://pubmed.ncbi.nlm.nih.gov/35184211
Background: Renal ultrasounds (RUS) are commonly ordered in hospitalized patients with acute kidney injury (AKI). Clinical decision support tools could be used to inform which patients may benefit from RUS to rule out hydronephrosis, however current
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::466aeb5f539b604129a1c89226684f5b
https://doi.org/10.21203/rs.2.10735/v2
https://doi.org/10.21203/rs.2.10735/v2
Autor:
Nathaniel C. Swinburne, Anthony Costa, Joshua B. Bederson, Joseph Lehar, Margaret Pain, Andres Su, Joseph J. Titano, J Mocco, Michael Cai, Javin Schefflein, Samuel K. Cho, Burton P. Drayer, Eric K. Oermann, Jun S. Kim, John R. Zech, Marcus A. Badgeley
Publikováno v:
Nature Medicine. 24:1337-1341
Rapid diagnosis and treatment of acute neurological illnesses such as stroke, hemorrhage, and hydrocephalus are critical to achieving positive outcomes and preserving neurologic function-'time is brain'1-5. Although these disorders are often recogniz
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3d71b60d251382af714d2b010b0e9c8e
https://doi.org/10.1038/s41591-018-0147-y
https://doi.org/10.1038/s41591-018-0147-y
Autor:
Javin Schefflein, Anthony Costa, Margaret Pain, Andres Su, Joseph J. Titano, John R. Zech, Marcus A. Badgeley, Eric K. Oermann, Joseph Lehar, Joshua B. Bederson
Publikováno v:
Radiology. 287:570-580
Purpose To compare different methods for generating features from radiology reports and to develop a method to automatically identify findings in these reports. Materials and Methods In this study, 96 303 head computed tomography (CT) reports were ob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17da14a104282bc3247f70aee2a19a75
https://doi.org/10.1148/radiol.2018171093
https://doi.org/10.1148/radiol.2018171093
Autor:
Joel T. Dudley, Bethany Percha, Michael V. McConnell, John R. Zech, Manway Liu, Marcus A. Badgeley, Benjamin S. Glicksberg, Luke Oakden-Rayner, Thomas M. Snyder, William Gale
Publikováno v:
npj Digital Medicine, Vol 2, Iss 1, Pp 1-10 (2019)
NPJ Digital Medicine
NPJ Digital Medicine
Hip fractures are a leading cause of death and disability among older adults. Hip fractures are also the most commonly missed diagnosis on pelvic radiographs, and delayed diagnosis leads to higher cost and worse outcomes. Computer-aided diagnosis (CA
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a39fb09ca00624225a5fbf1ca76ca95a
https://doi.org/10.1038/s41746-019-0105-1
https://doi.org/10.1038/s41746-019-0105-1
Autor:
Eric K. Oermann, Samuel K. Cho, Michael L Martini, Joseph J. Titano, Brett Marinelli, Martin Kang, Anthony Costa, John R. Zech
Publikováno v:
Radiol Artif Intell
PURPOSE: To determine if weakly supervised learning with surrogate metrics and active transfer learning can hasten clinical deployment of deep learning models. MATERIALS AND METHODS: By leveraging Liver Tumor Segmentation (LiTS) challenge 2017 public
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3556796f09f449d53c7cd5e2e325e46e
https://europepmc.org/articles/PMC8017413/
https://europepmc.org/articles/PMC8017413/