胡丹青

性别：男

毕业院校：浙江大学

学历：博士研究生毕业

学位：工学博士学位

在职信息：在岗

所在单位：人工智能学院（未来技术学院、人工智能产业学院）

办公地点：南京信息工程大学临江楼A1708

联系方式：danqinghu@nuist.edu.cn

   

个人简介


个人简介

      胡丹青，博士，南京信息工程大学人工智能学院（未来技术学院）讲师，2014年本科毕业于山东大学，2017年和2022年先后在浙江大学研究生毕业并取得硕士和博士学位。研究方向为医学人工智能、医学信息学、恶性肿瘤精准诊断及预后预测等。目前主持国家自然科学青年基金，参与北京市自然科学基金海淀原始创新重点项目、“十三五”国家重点研究专项精准医学研究项目以及国家自然科学基金面上项目等。在IEEE JBHI、AIM、JMIR、IJMI、IEEE EMBC等医学信息重要期刊会议发表论文18篇（第一作者15篇），申请发明专利11项（第一发明人授权4项），授权软件著作权4项，获中国中文信息学会CHIP2018最佳论文奖。



科研项目

  • 多模态数据时空融合的肺癌生长转移风险预测方法研究，国家自然科学基金青年基金，2025.01-2027.12，主持

  • 基于多期CT和血浆cfDNA多组学的人工智能肺癌早筛模型研发，北京市自然科学基金重点研究专题，2023.01-2025.12，参与单位负责人



招生信息

  • -常年招收人工智能专业专硕（专业型硕士）

  • -欢迎大二及以上本科生参与到我的科研项目，如果你想未来从事科研道路，我将帮助你学习如何开展学术研究，如何撰写学术论文和专利（如果你有自己的idea，我也可以为你提供你所需的帮助）

  • -欢迎联系我作为指导老师参与各种高水平科创竞赛，如“中国国际大学生创新大赛”、“全国大学生生物医学工程创新设计竞赛”、“挑战杯”等


如果你对课题组的研究方向具有浓厚的兴趣，对于利用人工智能技术解决临床领域的关键问题抱有憧憬，具有不断学习不怕失败的探索精神，不用犹豫和顾虑，十分欢迎与我联系~



研究方向

医学人工智能、医学信息学、肺癌全流程临床决策支持

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学术成果

Google Scholar: https://scholar.google.com/citations?user=yVk9ABwAAAAJ&hl=zh-CN 

2025

  • D. Hu, S. Zhang, Q. Liu, X. Zhu, and B. Liu, "Large Language Models in Summarizing Radiology Report Impressions for Lung Cancer in Chinese: Evaluation Study," Journal of Medical Internet Research, vol. 27, p. e65547, 2025.

2024

  • H. Su, B. Liu, X. Zhu, X. Lu, N. Wu, and D. Hu, "TGMT: A Terminology-Guided Multi-Task Approach for Lung Cancer CT Report Generation," in 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2024: IEEE, pp. 1-5. 

  • D. Hu, B. Liu, X. Zhu, X. Lu, and N. Wu, "Predicting Lymph Node Metastasis of Lung Cancer: A Two-stage Multimodal Data Fusion Approach," in 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2024: IEEE, pp. 1-4. 

  • D. Hu, B. Liu, X. Zhu, X. Lu, and N. Wu, "KAMLN: A Knowledge-aware Multi-label Network for Lung Cancer Complication Prediction," in 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2024: IEEE, pp. 1-5. 

  • D. Hu, B. Liu, X. Zhu, X. Lu, and N. Wu, "Zero-shot information extraction from radiological reports using ChatGPT," International Journal of Medical Informatics, vol. 183, p. 105321, 2024.

2023

  • D. Hu et al., "A Hierarchy-driven Multi-label Network with Label Constraints for Post-operative Complication Prediction of Lung Cancer," in 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2023: IEEE, pp. 1-6. 

  • D. Hu et al., "A Deep Multi-Task Network to Learn Tumor Pathological Representations for Lymph Node Metastasis Prediction," in MedInfo, 2023, pp. 906-910. 

  • D. Hu, S. Li, N. Wu, and X. Lu, "A Multi-Modal Heterogeneous Graph Forest to Predict Lymph Node Metastasis of Non-Small Cell Lung Cancer," IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 3, pp. 1216-1224, 2023, doi: 10.1109/JBHI.2022.3233387.

2022

  • H. Chen, H. Xiaoyuan, D. Hu, H. Duan, and X. Lu, "Automatic Extraction of Genomic Variants for Locating Precision Oncology Clinical Trials," in CHIP 2022, Singapore, 2023: Springer Nature Singapore, in Health Information Processing, pp. 109-123. 

  • D. Hu, H. Zhang, S. Li, H. Duan, N. Wu, and X. Lu, "An ensemble learning with active sampling to predict the prognosis of postoperative non-small cell lung cancer patients," BMC Medical Informatics and Decision Making, vol. 22, no. 1, p. 245, 2022/09/19 2022, doi: 10.1186/s12911-022-01960-0.

  • D. Hu, S. Li, H. Zhang, N. Wu, and X. Lu, "Using Natural Language Processing and Machine Learning to Preoperatively Predict Lymph Node Metastasis for Non–Small Cell Lung Cancer With Electronic Medical Records: Development and Validation Study,", JMIR Medical Informatics, vol. 10, no. 4, p. e35475, 2022, doi: 10.2196/35475.

  • Y. Chen, D. Hu, M. Li, H. Duan, and X. Lu, "Automatic SNOMED CT coding of Chinese clinical terms via attention-based semantic matching," International Journal of Medical Informatics, vol. 159, p. 104676, 2022/03/01/ 2022, doi: https://doi.org/10.1016/j.ijmedinf.2021.104676.

2021之前

  • H. Zhang*, D. Hu*, H. Duan, S. Li, N. Wu, and X. Lu, "A novel deep learning approach to extract Chinese clinical entities for lung cancer screening and staging," BMC Medical Informatics and Decision Making, vol. 21, no. 2, pp. 214-214, 2021, doi: 10.1186/s12911-021-01575-x.

  • D. Hu, H. Zhang, S. Li, Y. Wang, N. Wu, and X. Lu, "Automatic Extraction of Lung Cancer Staging Information From Computed Tomography Reports: Deep Learning Approach," JMIR Medical Informatics, vol. 9, no. 7, pp. e27955-e27955, 2021, doi: 10.2196/27955.

  • D. Hu, S. Li, Z. Huang, N. Wu, and X. Lu, "Predicting postoperative non-small cell lung cancer prognosis via long short-term relational regularization," Artificial Intelligence in Medicine, vol. 107, p. 101921, 2020/07/01/ 2020, doi: https://doi.org/10.1016/j.artmed.2020.101921.

  • D. Hu, W. Dong, X. Lu, H. Duan, K. He, and Z. Huang, "Evidential MACE prediction of acute coronary syndrome using electronic health records," BMC Medical Informatics and Decision Making, vol. 19, no. 2, p. 61, 2019/04/09 2019, doi: 10.1186/s12911-019-0754-7.

  • D. Hu, Z. Huang, T.-M. Chan, W. Dong, X. Lu, and H. Duan, "Acute coronary syndrome risk prediction based on GRACE risk score," in 16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017, August 21-25, 2017, Hangzhou, China, 2017, vol. 245: IOS Press BV, pp. 398-402

  • D. Hu, Z. Huang, T.-M. Chan, W. Dong, X. Lu, and H. Duan, "Utilizing Chinese Admission Records for MACE Prediction of Acute Coronary Syndrome," International Journal of Environmental Research and Public Health, vol. 13, no. 9, p. 912, 2016.


发明专利

  • 胡丹青，吴楠，程乐超，刘冰，一种层级聚类约束的多标签细粒度术后并发症预测装置，ZL 2023 1 0699832.6.

  • 胡丹青，朱晓峰，苏慧，一种集成自适应相似患者图的疾病预测装置，ZL 2023 1 0898736.4.

  • 胡丹青，程乐超，一种多模态图森林的肺癌淋巴结转移辅助诊断系统，ZL 2022 1 1375015.7.

  • 胡丹青，朱晓峰，苏慧，一种伪标签演变趋势正则的预后预测装置，ZL 2023 1 0791063.2.

  • 吕旭东，胡丹青，段会龙，非小细胞肺癌集成预后预测模型及其构建方法、装置及应用，ZL 2021 1 0500821.1.

  • 吕旭东，胡丹青，章宦耀，段会龙，基于多轮问答的CT影像报告信息抽取方法、装置、计算机设   备和存储介质，ZL 2021 1 1544922.5

  • 卢修生，苏慧，胡丹青，郭蕊，宋明黎，基于时空增强三维注意力重参数化的视频分类方法及装置，ZL 2023 1 1585233.8.

  • 苏慧，卢修生，胡丹青，郭蕊，弱监督语义分割方法、装置、设备和存储介质，ZL 2023 1 0636751.1.

教育经历

[1]   2018.9- 2022.6

浙江大学  |  生物医学工程  |  工学博士  |  博士研究生

[2]   2014.9- 2017.3

浙江大学  |  生物医学工程  |  工学硕士  |  硕士研究生

[3]   2010.9- 2014.6

山东大学  |  生物医学工程  |  工学学士  |  本科

工作经历

[1]   2025.2- 至今

南京信息工程大学  |  人工智能学院（未来技术学院）

[2]   2022.7- 2025.2

之江实验室  |  助理研究员

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