一、基本情况

姚钊，男，博士，湖南大学电气与信息工程学院助理教授，硕士研究生导师。本科毕业于河北工业大学，硕博毕业于复旦大学。主要研究方向为：超声图像的识别与生成；全片扫描病理图像分析；多模态医学图像分析。以第一作者/共同第一作者在Nature Communications，eBioMedicine等期刊发表多篇论文。担任Nature BME, IEEE JBHI, MICCAI等期刊和会议审稿人。

主页: https://yyyzzzhao.github.io

Google scholar: https://scholar.google.com/citations?hl=zh-CN&user=4s3to8IAAAAJ

二、研究方向

1）超声图像的生成；

2）全片扫描病理图像多示例学习；

3）医学图像多模态融合方法；

致力于开发计算机算法解决临床问题，与国内多家高水平三家医院保持良好合作。

三、教育工作经历

2024.06-至今 湖南大学，电气与信息工程学院，助理教授

2020.09-2024.06 复旦大学，电子信息，博士

2023.09-2024.04 香港理工大学，BME，联培

2017.09-2020.03 复旦大学，电子与信息工程，硕士

2013.09-2017.06 河北工业大学，电子信息工程，学士

四、代表性成果

[1] Zhao Yao*, Yuanyuan Wang, Jinhua Yu, Jianqiao Zhou, et.al. Virtual elastography ultrasound via generative adversarial network for breast cancer diagnosis. Nature Communications 14, 2023. (Nature子刊);

[2] Xueyi Zheng*, Zhao Yao*, Yuanyuan Wang, Jinhua Yu, Jianhua Zhou, et.al. Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer. Nature Communications 11, 2020. (Nature子刊，共一，ESI高被引);

[3] Yini Huang*, Zhao Yao*, Yuanyuan Wang, Jinhua Yu, Jianhua Zhou, et.al. Deep learning radiopathomics based on preoperative US images and biopsy whole slide images can distinguish between luminal and non-luminal tumors in early-stage breast cancers. eBioMedicine, 94, 2023. (The Lancet子刊，共一);

[4] Zhao Yao*, Jinhua Yu, Wenping Wang, et.al. Preoperative diagnosis and prediction of hepatocellular carcinoma: Radiomics analysis based on multi-modal ultrasound images. BMC Cancer, 18, 2018;

[5] Mengxin Tian*, Zhao Yao*, Jinhua Yu, Xuefei Wang, et al. DeepRisk network: an AI-based tool for digital pathology signature and treatment responsiveness of gastric cancer using whole-slide images. Journal of Translational Medicine, 22, 2024;

[6] Jieyang Jin*, Zhao Yao*, Jinhua Yu, Rongqin Zheng, et al. Deep learning radiomics model accurately predicts hepatocellular carcinoma occurrence in chronic hepatitis B patients: a five-year follow-up. American journal of cancer research, 11, 2021。