Integrated clinical and genomic models using machine-learning methods to predict the efficacy of paclitaxel-based chemotherapy in patients with advanced gastric cancer

Integrated clinical and genomic models using machine-learning methods to predict the efficacy of paclitaxel-based chemotherapy in patients with advanced gastric cancer

Abstract Background Paclitaxel is commonly used as a second-line therapy for advanced gastric cancer (AGC). The decision to proceed with second-line chemotherapy and select an appropriate regimen is critical for vulnerable patients with AGC progressing after first-line chemotherapy. However, no pred...

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Bibliographic Details
Main Authors: Yonghwa Choi, Jangwoo Lee, Keewon Shin, Ji Won Lee, Ju Won Kim, Soohyeon Lee, Yoon Ji Choi, Kyong Hwa Park, Jwa Hoon Kim
Format: Article
Language:English
Published: BMC 2024-04-01
Series:BMC Cancer
Subjects:
Advanced gastric cancer
Paclitaxel
Machine learning
Prediction
Artificial neural network
Online Access:https://doi.org/10.1186/s12885-024-12268-9

Internet

https://doi.org/10.1186/s12885-024-12268-9

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