Deep learning-assisted radiomics facilitates multimodal prognostication for personalized treatment strategies in low-grade glioma

Determining the optimal course of treatment for low grade glioma (LGG) patients is challenging and frequently reliant on subjective judgment and limited scientific evidence. Our objective was to develop a comprehensive deep learning assisted radiomics model for assessing not only overall survival in...

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Detalles Bibliográficos
Autores principales: Rauch, P., Stefanits, H., Aichholzer, M., Serra, C., Vorhauer, D., Wagner, H., Böhm, P., Hartl, S., Manakov, I., Sonnberger, M., Buckwar, E., Ruiz-Navarro, F., Heil, K., Glöckel, M., Oberndorfer, J., Spiegl-Kreinecker, S., Aufschnaiter-Hiessböck, K., Weis, S., Leibetseder, A., Thomae, W., Hauser, T., Auer, C., Katletz, S., Gruber, A., Gmeiner, M.
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/PMC10258197/
https://www.ncbi.nlm.nih.gov/pubmed/37302994
http://dx.doi.org/10.1038/s41598-023-36298-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10258197/
https://www.ncbi.nlm.nih.gov/pubmed/37302994
http://dx.doi.org/10.1038/s41598-023-36298-8

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