护理学院硕士研究生导师简介

姓名 张斌                       

职称 副研究员

导师类型  （科学学位硕士生导师、专业学位硕士生导师）

1. 受教育简历

2018.09-2021.06 暨南大学，影像医学与核医学，博士

2014.09-2017.06 南方医科大学，影像医学与核医学，硕士

2009.09-2014.06 南昌大学医学院，医学影像与核医学，学士

2. 工作简历

2023.08-至今 暨南大学附属第一医院，副研究员

2021.07-2023.07 暨南大学第一临床医学院，博士后

2017.08-2018.09 暨南大学附属第一医院，放射科住院医师

3. 任教课程

硕士课程《医学影像学》、博士课程《医学影像学与核医学进展》

4. 研究方向

医学人工智能与大数据分析

5. 主持及参与的主要课题

1. 国家自然科学基金青年项目，81801665，基于机器学习算法的影像组学模型多分类预测鼻咽癌治疗抵抗，2019.1-2021.12，21万元，结题，主持

2. 中国博士后科学基金会，第70批面上项目，2021M701425，基于多模态融合与类间一致性感知的局部晚期鼻咽癌预后评估及诱导化疗决策，2021.11-2023.7，8万元，结题，主持

3. 中国博士后科学基金会，第15批特别资助（站中），2022T150266，基于多维度标志物的局部晚期鼻咽癌远处转移风险预测及影像标志物生物学机制验证，2022.08-2023.07，18 万，结题，主持

4. 暨南大学科学技术协会2023年青年科技人才托举工程项目（第一层次），11623209，2023.01-2024.12，20万，结题，主持

5. 2023年国家重点研发计划，生物与信息融合（BT 与 IT 融合）重点专项，基于多尺度跨时空异构数据构建肿瘤乏氧数字孪生系统，2023YFF1204600，2024.01-2027.12，1800万元，在研，子课题负责人

6. 广东省卫生健康委, “广东特支计划”省卫生健康委（卫生健康人才）青年拔尖人才项目，0720240213, 基于数字孪生技术的鼻咽癌精准治疗系统构建及临床验证，2024-10 至 2027-09，50万元,，在研，主持

6. 广州市科学技术局, 2025年度基础与应用基础研究专题（科技菁英“领航”项目）, 2025A04J7006，基于数字病理的鼻咽癌三级淋巴结构空间异质性智能定量评价及其分子表型验证研究, 2025-01 至 2027-12，30万元, 在研, 主持

7. 生物活性分子与成药性优化全国重点实验室自由课题，基于STING介导乏氧改善的肿瘤放疗协同增效药物研发，202402017，2024.6-2026.5，50万元，在研，第3参与人

8. 国家自然科学基金面上项目，81871323，多模MRI影像组学定量评价鼻咽癌乏氧微环境及改善乏氧分子机制研究，2019.1-2022.12，57万元，结题，参与

9. 国家自然科学基金面上项目，81571664，鼻咽癌乏氧微环境影像学评估体系的构建及抑制HIF-1α放疗增敏分子机制研究，2016.1-2019.12，66万元，结题，参与

六、近年发表的主要论文及出版的专著

1. Zhang B, Tian J, Dong D, Gu DS, Dong YH, Zhang L, Lian ZY, Liu J, Luo XN, Pei SF, Mo XK, Huang WH, Ouyang FS, Guo BL, Liang L, Chen WB, Liang CH, Zhang SX. Radiomics Features of Multiparametric MRI as Novel Prognostic Factors in Advanced Nasopharyngeal Carcinoma. Clinical Cancer Research 2017; 23(15): 4259-4269.

2. Zhang B, He X, Ouyang FS, Gu DS, Dong YH, Zhang L, Mo XK, Huang WH, Tian J, Zhang SX. Radiomic machine-learning classifiers for prognostic biomarkers of advanced nasopharyngeal carcinoma. Cancer Letters 2017; 403:21-27.

3. Sun J, Wu X, Zhang X, Huang W, Zhong X, Li X, Xue K, Liu S, Chen X, Li W, Liu X, Shen H, You J, He W, Jin Z, Yu L, Li Y, Zhang S, Zhang B. Radiomic Model Associated with Tumor Microenvironment Predicts Immunotherapy Response and Prognosis in Patients with Locoregionally Advanced Nasopharyngeal Carcinoma. Research (Wash D C). 2025;8:0749.

4. You J, Huang Y, Ouyang L, Zhang X, Chen P, Wu X, Jin Z, Shen H, Zhang L, Chen Q, Pei S, Zhang B, Zhang S. Automated and reusable deep learning (AutoRDL) framework for predicting response to neoadjuvant chemotherapy and axillary lymph node metastasis in breast cancer using ultrasound images: A retrospective, multicentre study. EclinicalMedicine 2024; 69:102499.

5. Shen H, Huang Y, Yan W, Zhang C, Liang T, Yang D, Feng X, Liu S, Wang Y, Cao W, Cheng Y, Chen H, Ni Q, Wang F, You J, Jin Z, He W, Sun J, Yang D, Liu L, Cao B, Zhang X, Li Y, Pei S, Zhang S, Zhang B. Noninvasive Deep Learning System for Preoperative Diagnosis of Follicular-Like Thyroid Neoplasms Using Ultrasound Images: A Multicenter, Retrospective Study. Ann Surg. 2025 Jul 21. doi: 10.1097/SLA.0000000000006841

6. Liu S, Zou Y, Zhong M, Li T, Cao Y, Wang R, You J, Zhang S, Zhang B. Prognostic significance of MRI-defined sarcopenia in patients with nasopharyngeal carcinoma: A propensity score matched analysis of real-world data. Radiother Oncol. 2023;188:109904.

7. Zhang B, Li MM, Chen WH, Zhao JF, Chen WQ, Dong YH, Gong X, Chen QY, Zhang L, Mo XK, Luo XN, Tian J, Zhang SX. Association of Chemoradiotherapy Regimens and Survival Among Patients With Nasopharyngeal Carcinoma: A Systematic Review and Meta-analysis. JAMA Netw Open. 2019;2(10): e1913619.

8. Zhang B, Jin Z, Zhang S. A deep-learning model to assist thyroid nodule diagnosis and management. Lancet Digit Health 2021; 3(7):e410.

9. Zhang B, Tian J, Pei S, Chen Y, He X, Dong Y, Zhang L, Mo X, Huang W, Cong S, Zhang S. Machine Learning-Assisted System for Thyroid Nodule Diagnosis. Thyroid. 2019;29(6):858-867.

10. Jin Z, Pei S, Ouyang L, Zhang L, Mo X, Chen Q, You J, Chen L, Zhang B, Zhang S. Thy-Wise: An interpretable machine learning model for the evaluation of thyroid nodules. Int J Cancer 2022;151(12):2229-2243.

11. Yan J, Zhang B, Zhang S, Cheng J, Liu X, Wang W, Dong Y, Zhang L, Mo X, Chen Q, Fang J, Wang F, Tian J, Zhang S, Zhang Z. Quantitative MRI-based radiomics for noninvasively predicting molecular subtypes and survival in glioma patients. NPJ Precis Oncol 2021; 5(1):72.

12. Fang J, Zhang B, Wang S, Jin Y, Wang F, Ding YY, Chen QY, Chen LT, Li YY, Li MM, Chen ZZ, Liu LZ, Liu ZY, Tian J, Zhang SX. Association of MRI-derived radiomic biomarker with disease-free survival in patients with early-stage cervical cancer. Theranostics 2020; 10(5): 2284-2292.

13. Jin Z, Zhang S, Zhang L, Chen Q, Liu S, Zhang B. Artificial Intelligence Risk Model (Mirai) Delivers Robust Generalization and Outperforms Tyrer-Cuzick Guidelines in Breast Cancer Screening. J Clin Oncol 2022; 40(20):2280-2281.

14. Zhang B, Zhang S. Etirinotecan Pegol Treatment for Patients With Metastatic Breast Cancer and Brain Metastases. JAMA Oncol. 2022;8(11):1700.

15. Zhang B, Zhang J, Chen H, Chen L, Chen Q, Li M, Chen Z, You J, Yang K, Zhang S. Novel coronavirus disease 2019 (COVID-19): relationship between chest CT scores and laboratory parameters. Eur J Nucl Med Mol Imaging 2020;47(9): 2083-2089.

16. Zhang B, Huang W, Zhang S. Clinical Features and Outcomes of Coronavirus Disease 2019 (COVID-19) Patients With Chronic Hepatitis B Virus Infection. Clin Gastroenterol Hepatol. 2020;18(11):2633-2637.

17. Zhang B, Zhang S. Radiomics-derived morphological features predict pulmonary function response during lumacaftor/ivacaftor therapy in patients with cystic fibrosis. Eur Respir J 2022;60(1):2103077.

18. Zhang L, Zheng J, Jin Z, Chen Q, Liu S, Zhang B. The potential and challenges of radiomics in uncovering prognostic and molecular differences in interstitial lung disease associated with systemic sclerosis. Eur Respir J. 2022;59(6): 2102792.

19. Wu X, Zhang B. ChatGPT promotes healthcare: Current applications and potential challenges. Int J Surg. 2024;110(1):606-608.

20. Wu X, Zhang S, Zhang Z, Xu Z, Wang W, Jin Z, You J, Guo Y, Zhang L, Huang W, Wang F, Liu X, Yan D, Cheng J, Yan J, Zhang S, Zhang B. Biologically interpretable multi-task deep learning pipeline predicts molecular alterations, grade, and prognosis in glioma patients. Npj Precision Oncology 2024;8(1):181.

21. Liu X, Shen H, Zhang L, Huang W, Zhang S, Zhang B. Immunotherapy for recurrent or metastatic nasopharyngeal carcinoma. NPJ Precis Oncol. 2024;8(1):101.

22. Huang L, Wu XW, You JJ, Jin Z, He WL, Sun J, Shen H, Liu X, Yue X, Cai W, Zhang SX, Zhang B. Artificial Intelligence for Predicting Personalized Immunotherapy Outcomes in Cancer: A Comprehensive Review. Cancer Immunology Research.2025; 13(7): 964-977.

23. Zeng C, Wu X, Ouyang F, Guo B, Zhang X, Ma J, Zeng D, Zhang B. Perfusion Parameter Map Generation from 3 Phases of Computed Tomography Perfusion in Stroke Using Generative Adversarial Networks. Research (Wash D C). 2025;8:0689.  

24. Zhang M, Zhang B. Extracellular matrix stiffness: mechanisms in tumor progression and therapeutic potential in cancer. Exp Hematol Oncol. 2025;14(1):54.

七、重要社会任职（兼职）

广州市医学图像与生物信息智能分析重点实验室副主任

广东省医学生物工程学会医学影像分会秘书

广东省医学会肿瘤影像与大数据专委会青年学组委员  

广东省卒中学会医学影像分会第二届委员

中华医学会《数字医学与健康》杂志第一届编辑委员会通讯编委