A machine learning-based radiomics model for prediction of tumor mutation burden in gastric cancer

Purpose: To evaluate the potential of machine learning (ML)-based radiomics approach for predicting tumor mutation burden (TMB) in gastric cancer (GC). Methods: The contrast enhanced CT (CECT) images with corresponding clinical information of 256 GC patients were retrospectively collected. Patients...

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Detalles Bibliográficos
Autores principales: Ma, Tingting, Zhang, Yuwei, Zhao, Mengran, Wang, Lingwei, Wang, Hua, Ye, Zhaoxiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Genetics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10657897/
https://www.ncbi.nlm.nih.gov/pubmed/38028587
http://dx.doi.org/10.3389/fgene.2023.1283090

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10657897/
https://www.ncbi.nlm.nih.gov/pubmed/38028587
http://dx.doi.org/10.3389/fgene.2023.1283090

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