Machine learning to predict myocardial injury and death after non‐cardiac surgery

Autor: J. M. Nolde, M. P. Schlaich, D. I. Sessler, A. Mian, T. B. Corcoran, C. K. Chow, M. T. V. Chan, F. K. Borges, M. H. McGillion, P. S. Myles, N. L. Mills, P. J. Devereaux, G. S. Hillis

Publikováno v: Nolde, J M, Schlaich, M P, Sessler, D I, Mian, A, Corcoran, T B, Chow, C K, Chan, M T V, Borges, F K, McGillion, M H, Myles, P S, Mills, N L, Devereaux, P J & Hillis, G S 2023, ' Machine learning to predict myocardial injury and death after non-cardiac surgery ', Anaesthesia: Peri-operative medicine, critical care and pain . https://doi.org/10.1111/anae.16024

Myocardial injury due to ischaemia within 30 days of non-cardiac surgery is prognostically relevant. We aimed to determine the discrimination, calibration, accuracy, sensitivity and specificity of single-layer and multiple-layer neural networks for m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::85d25e4733dc631830ec8545f54c8cdb
https://doi.org/10.1111/anae.16024