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

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 evaluates a tr...

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Detalles Bibliográficos
Autores principales: Khader, Firas, Kather, Jakob Nikolas, Müller-Franzes, Gustav, Wang, Tianci, Han, Tianyu, Tayebi Arasteh, Soroosh, Hamesch, Karim, Bressem, Keno, Haarburger, Christoph, Stegmaier, Johannes, Kuhl, Christiane, Nebelung, Sven, Truhn, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10314902/
https://www.ncbi.nlm.nih.gov/pubmed/37393383
http://dx.doi.org/10.1038/s41598-023-37835-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10314902/
https://www.ncbi.nlm.nih.gov/pubmed/37393383
http://dx.doi.org/10.1038/s41598-023-37835-1

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