This paper is in the following e-collection/theme issue:

Artificial Intelligence (726) Machine Learning (1059) Clinical Information and Decision Making (954) Clinical Informatics (581)

Published on in Vol 24 , No 6 (2022) :June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34295, first published .
Machine Learning–Based Prediction Models for Different Clinical Risks in Different Hospitals: Evaluation of Live Performance

Machine Learning–Based Prediction Models for Different Clinical Risks in Different Hospitals: Evaluation of Live Performance

Machine Learning–Based Prediction Models for Different Clinical Risks in Different Hospitals: Evaluation of Live Performance

Authors of this article:

Hong Sun 1 Author Orcid Image ;   Kristof Depraetere 1 Author Orcid Image ;   Laurent Meesseman 1 Author Orcid Image ;   Patricia Cabanillas Silva 1 Author Orcid Image ;   Ralph Szymanowsky 1 Author Orcid Image ;   Janis Fliegenschmidt 2 Author Orcid Image ;   Nikolai Hulde 2 Author Orcid Image ;   Vera von Dossow 2 Author Orcid Image ;   Martijn Vanbiervliet 1 Author Orcid Image ;   Jos De Baerdemaeker 1 Author Orcid Image ;   Diana M Roccaro-Waldmeyer 1 Author Orcid Image ;   Jörg Stieg 1 Author Orcid Image ;   Manuel Domínguez Hidalgo 1 Author Orcid Image ;   Fried-Michael Dahlweid 1 Author Orcid Image
Article Authors Cited by (2) Tweetations (11) Metrics

Journals

  1. Fliegenschmidt J, Hulde N, Gedinha Preising M, Ruggeri S, Szymanowsky R, Meesseman L, Sun H, Dahlweid M, von Dossow V. Leveraging artificial intelligence for the management of postoperative delirium following cardiac surgery. European Journal of Anaesthesiology Intensive Care 2023;2(1):e0010 View
  2. Matsumoto K, Nohara Y, Sakaguchi M, Takayama Y, Fukushige S, Soejima H, Nakashima N. Delirium Prediction Using Machine Learning Interpretation Method and Its Incorporation into a Clinical Workflow. Applied Sciences 2023;13(3):1564 View