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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...
Autores principales: | Murakami, Yuji, Kawahara, Daisuke, Tani, Shigeyuki, Kubo, Katsumaro, Katsuta, Tsuyoshi, Imano, Nobuki, Takeuchi, Yuki, Nishibuchi, Ikuno, Saito, Akito, Nagata, Yasushi |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
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 |
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