Machine learning for predicting pathological complete response in patients with locally advanced rectal cancer after neoadjuvant chemoradiotherapy

For patients with locally advanced rectal cancer (LARC), achieving a pathological complete response (pCR) after neoadjuvant chemoradiotherapy (CRT) provides them with the optimal prognosis. However, no reliable prediction model is presently available. We evaluated the performance of an artificial ne...

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Detalles Bibliográficos
Autores principales: Huang, Chun-Ming, Huang, Ming-Yii, Huang, Ching-Wen, Tsai, Hsiang-Lin, Su, Wei-Chih, Chang, Wei-Chiao, Wang, Jaw-Yuan, Shi, Hon-Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7387337/
https://www.ncbi.nlm.nih.gov/pubmed/32724164
http://dx.doi.org/10.1038/s41598-020-69345-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7387337/
https://www.ncbi.nlm.nih.gov/pubmed/32724164
http://dx.doi.org/10.1038/s41598-020-69345-9

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