日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

An interpretable AI system reduces false-positive MRI diagnoses by stratifying high-risk breast lesions

一种可解释的人工智能系统通过对高风险乳腺病变进行分层,减少了MRI诊断的假阳性结果。

Liang, Yanting; Wei, Zhitao; Dai, Yi; Chen, Xiaobo; Du, Siyao; Wong, Chinting; Xu, Zeyan; Gao, Weibo; Han, Chu; Chen, Kexin; Han, Ke; Liao, Jiayi; Zhang, Yuelang; Zhang, Lina; Liu, Zaiyi; Zhang, Yan; Wang, Ying; Liang, Changhong; Shi, Zhenwei

Pathogenomic analysis reveals clinically relevant epithelial-mesenchymal plasticity in esophageal squamous cell carcinoma

病理基因组学分析揭示了食管鳞状细胞癌中具有临床意义的上皮-间质可塑性

Chen, Ruzhen; Xie, Chenyi; Ning, Ziyu; Yang, Meng; Su, Zezhuo; Chen, Jiahui; Du, Kunheng; Hu, Yihuai; Han, Chu; Zhang, Shaojun; Zhang, Qingling; Liu, Meng; Liu, Zaiyi

Longitudinal MRI-based deep learning model for predicting pathological complete response in breast cancer: a multicenter, retrospective cohort study

基于纵向磁共振成像的深度学习模型预测乳腺癌病理完全缓解:一项多中心回顾性队列研究

Huang, Xu; Xu, Zeyan; Zhao, Yingnan; Wang, Ying; Liu, Yu; Hu, Wei; Zhao, Ke; Yao, Lisha; He, Jiahui; Yu, Yifan; Deng, Tianpeng; Wu, Lei; Zhang, Wu; Liang, Changhong; Liu, Zaiyi

Artificial intelligence-based tumor-stroma ratio quantification reveals prognostic value and stromal-driven immunosuppression in colorectal cancer: an international validation study

基于人工智能的肿瘤-基质比率定量分析揭示了其在结直肠癌中的预后价值和基质驱动的免疫抑制:一项国际验证研究

Ye, Huifen; Zhao, Ke; Cui, Yanfen; Li, Zhenhui; Zhang, Huan; Zhong, Min-Er; Fan, Chuanwen; Huang, Haitao; Hawkins, Nicholas J; Ward, Robyn L; Sun, Xiao-Feng; Song, Jinming; Liu, Zaiyi; Jonnagaddala, Jitendra; Tong, Tong; Yao, Su

Network models for bridging denoising and identifying spatial domains of spatially resolved transcriptomics

用于桥接空间分辨转录组学去噪和识别空间域的网络模型

Wang, Haiyue; Zhang, Wensheng; Liu, Zaiyi; Ma, Xiaoke

Multiparametric MRI-based habitat analysis integrating deep learning and radiomics for predicting preoperative Ki-67 expression level in breast cancer

基于多参数磁共振成像的生境分析,结合深度学习和放射组学,用于预测乳腺癌术前Ki-67表达水平

Wang, Yuqian; Zhang, Yue; Liu, Zaiyi; Xiong, Yiming; Li, Mifang; Zhang, Lingyan; Shi, Zhenwei

CeLLTra: aligning cell names with gene expression via a pathway-informed transformer

CeLLTra:通过通路信息转换器将细胞名称与基因表达进行匹配

Li, Zhao; Zheng, Zaiyi; Li, Rongbin; Chen, Wenbo; Yang, Yuntao; Ali, Meer A; Li, Jundong; Zheng, W Jim

BEEx Is an Open-Source Tool That Evaluates Batch Effects in Medical Images to Enable Multicenter Studies

BEEx 是一款开源工具,用于评估医学图像中的批次效应,以支持多中心研究。

Wu, Yuxin; Xu, Xiongjun; Cheng, Yuan; Zhang, Xiuming; Liu, Fanxi; Li, Zhenhui; Hu, Lei; Madabhushi, Anant; Gao, Peng; Liu, Zaiyi; Lu, Cheng

Multiomic integration reveals subtype-specific predictors of neoadjuvant treatment response in breast cancer

多组学整合揭示乳腺癌新辅助治疗反应的亚型特异性预测因子

Mo, Zongchao; Yang, Mei; Zhu, Zhihan; Wang, Minghao; Wang, Haoyu; Zhang, Zhanye; Lyu, Shanshan; Xu, Fangping; Shang, Haixia; Lin, Huan; Xu, Zeyan; Li, Suyun; Chen, Xiaobo; Wang, Kun; Liang, Changhong; Wang, Jiguang; Liu, Zaiyi

Deep learning-based prediction of axillary pathological complete response in patients with breast cancer using longitudinal multiregional ultrasound

基于深度学习的纵向多区域超声预测乳腺癌患者腋窝病理完全缓解

Liu, Yu; Wang, Ying; Huang, Jiaxin; Pei, Shufang; Wang, Yuxiang; Cui, Yanfen; Yan, Lifen; Yao, Mengxia; Wang, Yumeng; Zhu, Zejun; Huang, Chunwang; Liu, Zaiyi; Liang, Changhong; Shi, Jiayao; Li, Zhenhui; Pei, Xiaoqing; Wu, Lei