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

• Main Authors: Hong Sun (Author), Kristof Depraetere (Author), Laurent Meesseman (Author), Patricia Cabanillas Silva (Author), Ralph Szymanowsky (Author), Janis Fliegenschmidt (Author), Nikolai Hulde (Author), Vera von Dossow (Author), Martijn Vanbiervliet (Author), Jos De Baerdemaeker (Author), Diana M Roccaro-Waldmeyer (Author), Jörg Stieg (Author), Manuel Domínguez Hidalgo (Author), Fried-Michael Dahlweid (Author)
• Format: Book
• Published: JMIR Publications, 2022-06-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

BackgroundMachine learning algorithms are currently used in a wide array of clinical domains to produce models that can predict clinical risk events. Most models are developed and evaluated with retrospective data, very few are evaluated in a clinical workflow, and even fewer report performances in...