NSF4SL: negative-sample-free contrastive learning for ranking synthetic lethal partner genes in human cancers. - Shike Wang; Yimiao Feng; Xin Liu 027; Yong Liu 020; Min Wu 008; Jie Zheng 002 (Bioinform., 2022)

KR4SL: knowledge graph reasoning for explainable prediction of synthetic lethality. - Ke Zhang; Min Wu 008; Yong Liu 020; Yimiao Feng; Jie Zheng 002 (Bioinform., 2023)

Prompt-based Generation of Natural Language Explanations of Synthetic Lethality for Cancer Drug Discovery. - Ke Zhang; Yimiao Feng; Jie Zheng 002 (LREC/COLING, 2024)

CellSeg2TLS: A Deep Learning Framework for Predicting the Maturation of Tertiary Lymphoid Structures in Pathology Images. - Yang Yang; Mei Xie; Yimiao Feng; Xueheng Lv; Jialin Song; Xinying Xue; Jie Zheng (ISBI, 2024)

Early tumor volume change as a novel CT RECIST indicator for predicting pathological response and prognosis in NSCLC patients undergoing immunotherapy. - Fan Xu; Mei Xie; Xuwen Lin; Jie Gao; Xidong Ma; Yang Yang; Zhiqiang Xue; Chongchong Wu; Tianjiao Jiang; Yimiao Feng; Jialin Song; Yuanyong Wang; et al. (Biomed. Signal Process. Control., 2025)