The following publications are possibly variants of this publication:
- Computer-aided prediction of axillary lymph node status in breast cancer using tumor surrounding tissue features in ultrasound imagesWoo Kyung Moon, Yan-Wei Lee, Yao-Sian Huang, Su-Hyun Lee, Min Sun Bae, Ann Yi, Chiun-Sheng Huang, Ruey-Feng Chang. cmpb, 146:143-150, 2017. [doi]
- Prediction of axillary lymph node metastasis in primary breast cancer patients using a decision tree-based modelMasahiro Takada, Masahiro Sugimoto, Yasuhiro Naito, Hyeong-Gon Moon, Wonshik Han, Dong-Young Noh, Masahide Kondo, Katsumasa Kuroi, Hironobu Sasano, Takashi Inamoto, Masaru Tomita, Masakazu Toi. midm, 12:54, 2012. [doi]
- Axillary lymph node metastasis status prediction of early-stage breast cancer using convolutional neural networksYan-Wei Lee, Chiun-Sheng Huang, Chung-Chih Shih, Ruey-Feng Chang. cbm, 130:104206, 2021. [doi]
- Deep Learning Radiomics of Preoperative Breast MRI for Prediction of Axillary Lymph Node Metastasis in Breast CancerYanhong Chen, Lijun Wang, Xue-dong, Ran Luo, Yaqiong Ge, Huanhuan Liu, Yuzhen Zhang, Dengbin Wang. jdi, 36(4):1323-1331, August 2023. [doi]
- Axillary lymph node metastasis in pure mucinous carcinoma of breast: clinicopathologic and ultrasonographic featuresNa Li, Jia-Wei Li, Yu Qian, Ya-Jing Liu, Xiu-Zhu Qi, Ya-Ling Chen, Yi Gao, Cai Chang. bmcmi, 24(1):108, December 2024. [doi]