Assessing optimal methods for transferring machine learning models to low-volume and imbalanced clinical datasets: experiences from predicting outcomes of Danish trauma patients

• Principais autores: Andreas Skov Millarch (Autor), Alexander Bonde (Autor), Mikkel Bonde (Autor), Kiril Vadomovic Klein (Autor), Fredrik Folke (Autor), Søren Steemann Rudolph (Autor), Martin Sillesen (Autor)
• Formato: Livro
• Publicado em: Frontiers Media S.A., 2023-11-01T00:00:00Z.
• Assuntos: article
• Acesso em linha: Connect to this object online.

IntroductionAccurately predicting patient outcomes is crucial for improving healthcare delivery, but large-scale risk prediction models are often developed and tested on specific datasets where clinical parameters and outcomes may not fully reflect local clinical settings. Where this is the case, wh...