Identifying and Predicting Postoperative Infections Based on Readily Available Electronic Health Record Data

Posted on 16/12/202417/12/2024 by Laurens Schinkelshoek

Authors: S.L. van der Meijden, A.M. van Boekel, L.J. Schinkelshoek, H. Goor, M.G.J. de Boer, E.W. Steyerberg, B.F. Geerts, M.S. Arbous
Journal: Studies in Health Technology and Informatics
Year: 2023

Recent posts

Development and validation of artificial intelligence models for early detection of postoperative infections (PERISCOPE): a multicentre study using electronic health record data

16/12/2024

Authors: S.L. van der Meijden, A.M. van Boekel, L.J. Schinkelshoek, [...]

Systematic evaluation of machine learning models for postoperative surgical site infection prediction

16/12/2024

Authors: A.M. van Boekel S.L. van der Meijden, M.S. Arbous, [...]

Automated Identification of Postoperative Infections to Allow Prediction and Surveillance Based on Electronic Health Record Data: Scoping Review

16/12/2024

Authors: S.L. van der Meijden, A.M. van Boekel, H. Goor, [...]