Tseng, H.-C.; Shen, C.-Y.; Kao, P.-F.; Chuang, C.-Y.; Yan, D.-Y.; Liao, Y.-H.; Lu, X.-P.; Sheu, T.-J.; Shen, W.-C.
Prediction of Persistent Tumor Status in Nasopharyngeal Carcinoma Post-Radiotherapy-Related Treatment: A Machine Learning Approach. Cancers 2025, 17, 96.
https://doi.org/10.3390/cancers17010096
AMA Style
Tseng H-C, Shen C-Y, Kao P-F, Chuang C-Y, Yan D-Y, Liao Y-H, Lu X-P, Sheu T-J, Shen W-C.
Prediction of Persistent Tumor Status in Nasopharyngeal Carcinoma Post-Radiotherapy-Related Treatment: A Machine Learning Approach. Cancers. 2025; 17(1):96.
https://doi.org/10.3390/cancers17010096
Chicago/Turabian Style
Tseng, Hsien-Chun, Chao-Yu Shen, Pan-Fu Kao, Chun-Yi Chuang, Da-Yi Yan, Yi-Han Liao, Xuan-Ping Lu, Ting-Jung Sheu, and Wei-Chih Shen.
2025. "Prediction of Persistent Tumor Status in Nasopharyngeal Carcinoma Post-Radiotherapy-Related Treatment: A Machine Learning Approach" Cancers 17, no. 1: 96.
https://doi.org/10.3390/cancers17010096
APA Style
Tseng, H.-C., Shen, C.-Y., Kao, P.-F., Chuang, C.-Y., Yan, D.-Y., Liao, Y.-H., Lu, X.-P., Sheu, T.-J., & Shen, W.-C.
(2025). Prediction of Persistent Tumor Status in Nasopharyngeal Carcinoma Post-Radiotherapy-Related Treatment: A Machine Learning Approach. Cancers, 17(1), 96.
https://doi.org/10.3390/cancers17010096
