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NPJ Breast Cancer|November 23, 2022
Predicting neoadjuvant chemotherapy benefit using deep learning from stromal histology in breast cancerFengling Li, Yongquan Yang, Yani Wei, et al.
BMC Cancer|August 29, 2024
Pathology diagnosis of intraoperative frozen thyroid lesions assisted by deep learningTingting He, Shanshan Shi, Yiqing Liu, et al.
Medical Image Analysis|December 12, 2025
Diagnostic text-guided representation learning in hierarchical classification for pathological whole slide imageJiawen Li, Qiehe Sun, Renao Yan, et al.
NPJ Precision Oncology|July 15, 2025
AI-powered prediction model for neoadjuvant chemotherapy efficacy: comprehensive analysis of breast cancer histological imagesFengling Li, Yani Wei, Wenchuan Zhang, et al.
Human Pathology|June 13, 2025
Female Reproductive Tract Inflammatory Myofibroblastic Tumor (IMT): A Comprehensive Analysis of Clinicopathological and Genomic Features in a Case Series, Including the Identification of SERPINE1-ALK Fusion in the Fallopian TubeTing Lei, Bingbing Liu, Yani Wei, et al.
The Journal of Pathology|January 7, 2026
Integration of histopathological characteristics by machine learning improves the prediction of neoadjuvant immunochemotherapy response in triple-negative breast cancerXunxi Lu, Bin Luo, Yani Wei, et al.
Iscience|September 10, 2024
A deep learning method for predicting the origins of cervical lymph node metastatic cancer on digital pathological imagesRunliang Zheng, Xuenian Wang, Lianghui Zhu, et al.
Medcomm|July 6, 2026
Development and Validation of a Pathomics Model for Prognosis Prediction in Neoadjuvant Therapy-Treated Breast Cancer: A Retrospective, Multicenter StudyYani Wei, Wei Lou, Zongbo Han, et al.
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