Predicting the Local Response of Esophageal Squamous Cell Carcinoma to Neoadjuvant Chemoradiotherapy by Radiomics with a Machine Learning Method Using (18)F-FDG PET Images

Background: This study aimed to propose a machine learning model to predict the local response of resectable locally advanced esophageal squamous cell carcinoma (LA-ESCC) treated by neoadjuvant chemoradiotherapy (NCRT) using pretreatment 18-fluorodeoxyglucose positron emission tomography (FDG PET) i...

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Detalles Bibliográficos
Autores principales: Murakami, Yuji, Kawahara, Daisuke, Tani, Shigeyuki, Kubo, Katsumaro, Katsuta, Tsuyoshi, Imano, Nobuki, Takeuchi, Yuki, Nishibuchi, Ikuno, Saito, Akito, Nagata, Yasushi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8227132/
https://www.ncbi.nlm.nih.gov/pubmed/34200332
http://dx.doi.org/10.3390/diagnostics11061049

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8227132/
https://www.ncbi.nlm.nih.gov/pubmed/34200332
http://dx.doi.org/10.3390/diagnostics11061049

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