Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Anton H van der Vegt"'
Autor:
Amir Kamel Rahimi, Oliver Pienaar, Moji Ghadimi, Oliver J Canfell, Jason D Pole, Sally Shrapnel, Anton H van der Vegt, Clair Sullivan
Publikováno v:
Journal of Medical Internet Research, Vol 26, p e49655 (2024)
BackgroundEfforts are underway to capitalize on the computational power of the data collected in electronic medical records (EMRs) to achieve a learning health system (LHS). Artificial intelligence (AI) in health care has promised to improve clinical
Externí odkaz:
https://doaj.org/article/8a7a95e2fa2d4035868d6c4834c5f0c4
Autor:
Amir Kamel Rahimi, Moji Ghadimi, Anton H. van der Vegt, Oliver J. Canfell, Jason D. Pole, Clair Sullivan, Sally Shrapnel
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 23, Iss 1, Pp 1-14 (2023)
Abstract Background There are many Machine Learning (ML) models which predict acute kidney injury (AKI) for hospitalised patients. While a primary goal of these models is to support clinical decision-making, the adoption of inconsistent methods of es
Externí odkaz:
https://doaj.org/article/584cf1b56c7f45e58bb64a78fe233faf
Autor:
Anton H van der Vegt, Ian A Scott, Krishna Dermawan, Rudolf J Schnetler, Vikrant R Kalke, Paul J Lane
Publikováno v:
Journal of the American Medical Informatics Association.
Objective To derive a comprehensive implementation framework for clinical AI models within hospitals informed by existing AI frameworks and integrated with reporting standards for clinical AI research. Materials and Methods (1) Derive a provisional i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dd6bf1f4fc925c9527fb3cd2f3412587
https://doi.org/10.1093/jamia/ocad088
https://doi.org/10.1093/jamia/ocad088
Autor:
Anton H van der Vegt, Ian A Scott, Krishna Dermawan, Rudolf J Schnetler, Vikrant R Kalke, Paul J Lane
Publikováno v:
Journal of the American Medical Informatics Association.
Objective To retrieve and appraise studies of deployed artificial intelligence (AI)-based sepsis prediction algorithms using systematic methods, identify implementation barriers, enablers, and key decisions and then map these to a novel end-to-end cl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::27155b5ee421b91b59e98cba7704e6eb
https://doi.org/10.1093/jamia/ocad075
https://doi.org/10.1093/jamia/ocad075
Autor:
Han Chang Lim, Jodie A. Austin, Anton H. van der Vegt, Amir Kamel Rahimi, Oliver J. Canfell, Jayden Mifsud, Jason D. Pole, Michael A. Barras, Tobias Hodgson, Sally Shrapnel, Clair M. Sullivan
Publikováno v:
Applied clinical informatics. 13(2)
Objective A learning health care system (LHS) uses routinely collected data to continuously monitor and improve health care outcomes. Little is reported on the challenges and methods used to implement the analytics underpinning an LHS. Our aim was to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::302efa76c246150ceb1beb05019de769
https://pubmed.ncbi.nlm.nih.gov/35388447
https://pubmed.ncbi.nlm.nih.gov/35388447