Medical transformer for multimodal survival prediction in intensive care: integration of imaging and non-imaging data

Medical transformer for multimodal survival prediction in intensive care: integration of imaging and non-imaging data

Abstract When clinicians assess the prognosis of patients in intensive care, they take imaging and non-imaging data into account. In contrast, many traditional machine learning models rely on only one of these modalities, limiting their potential in medical applications. This work proposes and evalu...

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Bibliographic Details
Main Authors: Firas Khader, Jakob Nikolas Kather, Gustav Müller-Franzes, Tianci Wang, Tianyu Han, Soroosh Tayebi Arasteh, Karim Hamesch, Keno Bressem, Christoph Haarburger, Johannes Stegmaier, Christiane Kuhl, Sven Nebelung, Daniel Truhn
Format: Article
Language:English
Published: Nature Portfolio 2023-07-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-37835-1

Internet

https://doi.org/10.1038/s41598-023-37835-1

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