Predicting Rectal Cancer Response to Total Neoadjuvant Treatment Using an Artificial Intelligence Model Based on Magnetic Resonance Imaging and Clinical Data

PURPOSE: To develop a model for predicting response to total neoadjuvant treatment (TNT) for patients with locally advanced rectal cancer (LARC) based on baseline magnetic resonance imaging (MRI) and clinical data using artificial intelligence methods. METHODS: Baseline MRI and clinical data were cu...

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Detalles Bibliográficos
Autores principales: Ouyang, Ganlu, Chen, Zhebin, Dou, Meng, Luo, Xu, Wen, Han, Deng, Xiangbing, Meng, Wenjian, Yu, Yongyang, Wu, Bing, Jiang, Dan, Wang, Ziqiang, Yao, Yu, Wang, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Novel applications of Artificial Intelligence in cancer research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10338728/
https://www.ncbi.nlm.nih.gov/pubmed/37431270
http://dx.doi.org/10.1177/15330338231186467

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10338728/
https://www.ncbi.nlm.nih.gov/pubmed/37431270
http://dx.doi.org/10.1177/15330338231186467

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