团队简介:
澳门新葡萄新京app官网智能医学计算团队多年来致力于人工智能与医学健康交叉领域的前沿科学技术研究与应用。团队在机器学习、模式识别、数据挖掘、智能诊疗、工业软件、大模型、知识图谱等关键共性技术的研究与应用持续深耕,形成特色鲜明且聚焦前沿的医工交叉结合领域创新科研与人才培养平台。
团队拥有一支结构合理、科研实力过硬的教师队伍,现有教授1人,副教授2人,青年百人特聘副教授1人,青年百人讲师1人,研究生50余人。团队先后主持了多项国家重点研发计划项目、国家自然科学基金、广东省自然科学基金和广东省省级科技计划等项目,并在人工智能领域的顶级刊物与国际会议,如IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)、IEEE Transactions on Neural Networks and Learning Systems (TNNLS)、IEEE Transactions on Image Processing (TIP)、IEEE Transactions on Cybernetics (TCYB)、Advanced Science、IEEE Intelligent Systems、IEEE Transactions on Computational Social Systems、Pattern Recognition、AAAI Conference on Artificial Intelligence (AAAI)、ACM International Conference on Information and Knowledge Management(CIKM)等发表科研论文90余篇,并授权国家发明专利20余件。
成员简介:
曾安(团队负责人),女,博士后、教授、博士生导师、国家重点研发计划首席科学家。毕业于华南理工大学获得计算机应用技术专业,工学博士学位,现任澳门新葡萄新京app官网计算机学院副院长。曾于2008年9月至2010年8月在加拿大达尔豪斯大学计算机学院和医学院开展博士后研究工作;于2016年12月至2017年12月期间作为第17批博士服务团成员赴贵州财经大学挂职锻炼,挂任校长助理、大数据金融学院副院长;主持国家重点研发计划项目1项、国家自然科学基金2项、广东省自然科学基金2项、广东省省级科技计划项目1项,广州市科技计划项目1项等。在《IEEE Journal of Biomedical and Health Informatics》、《IEEE Transactions on Neural Networks and Learning Systems》、《Advanced Science》、《IEEE Intelligent Systems》、《IEEE Transactions on Computational Social Systems》和《电子学报》等刊物上发表论文50余篇。广东省工业软件学会秘书长、中国生物医学工程学会人工智能分会(委员)、广东省生物医学工程学会理事、CCF协同计算专委会(委员)、CCF人工智能专委会通讯委员、中国人工智能学会生物信息学与人工生命专业委员会(委员)。主要从事人工智能、机器学习、大数据分析与挖掘、深度学习和知识图谱等理论研究及其在健康医疗大数据和疾病辅助诊断等领域的应用研究。
张逸群,男,博士、博士后、副教授、IEEE会员、深圳市高层次专业人才。2013年于华南理工大学生物医学工程专业取得学士学位,2014和2019年分别于香港浸会大学计算机科学系取得硕士和博士学位,并随后开展博士后研究工作一年。目前已在人工智能和机器学习领域的顶级国际期刊和会议如 《IEEE Transactions on Pattern Analysis and Machine Intelligence》(TPAMI)、《IEEE Transactions on Cybernetics》(TCYB)、《IEEE Transactions on Neural Networks and Learning Systems》(TNNLS)、“AAAI Conference on Artificial Intelligence (AAAI)”、“International Joint Conference on Artificial Intelligence (IJCAI)”,以及知名国际期刊和会议等发表论文十余篇。张逸群博士曾在香港浸会大学获得多项奖学金和科研奖励,还于2018和2019年分别获得ISMIS’2018国际会议最佳论文奖和 IEEE 智能计算分会(香港)的科研成果竞赛冠军。目前担任多个国际期刊和会议如TNNLS、 TCYB、 TETCI、 Pattern Recognition、 Neurocomputing、 ICDM、 PAKDD、 IJCNN、 ICPR、 ICIP 等的审稿人,以及担任期刊Frontiers in Computer Science的专题“Advances in Long-Tail Learning”编委成员。当前从事的研究方向是无监督机器学习、异构特征数据分析、流数据分析、以及上述技术在医疗健康数据分析中的应用。
杨宝瑶,女,博士、博士后、副教授。2014年于华南理工大学计算机科学与工程学院获取学士学位;同年作为优秀毕业生,前往香港浸会大学直接攻读博士,于2018年取得博士学位;2019年前往日本东京大学和日本理研(RIKEN)进行为期两个月的访问学习,也曾访问美国马里兰大学、日本京都大学等世界级顶尖学府,并且在人工智能领域主流国际会议“AAAI Conference on Artificial Intelligence”上展示了多项研究成果,紧贴人工智能最前沿的先进技术,积累了丰富的人工智能研究经验。在机器学习、模式识别、医疗信息智能化等方面取得了丰富的研究成果,在《IEEE Transactions on Cybernetics》(TCYB)、《IEEE Transactions on Image Processing》(TIP)、《IEEE Transactions on Information Forensics and Security》(TIFS)、《Pattern Recognition》(PR)、《IEEE Transactions on Neural Networks and Learning Systems》(TNNLS)等国际知名学术刊物上发表了多篇学术论文,还在“AAAI Conference on Artificial Intelligence(AAAI)”、“IEEE Winter Conference on Applications of Computer Vision (WACV)”、“ACM International Conference on Information and Knowledge Management(CIKM)”、“International Conference on Medical Image Computing and Computer Assisted Intervention(MICCAI)”等国际主流学术会议上发表了多篇论文。担任多个国际期刊和会议如CVPR、ICCV、TNNLS、TMM、MICCAI、TCYB、Pattern Recognition等的审稿人。研究方向是机器学习、联邦学习、迁移学习、健康/医学信息学、医学图像处理。
姬玉柱,男,博士、博士后,现为澳门新葡萄新京app官网计算机学院青年百人特聘副教授。2011年于解放军信息工程大学计算机专业取得学士学位,2014和2019年分别于哈尔滨工业大学计算机科学系取得硕士和博士学位,并于2020年赴新加坡南洋理工大学开展博士后研究工作。目前已在人工智能领域的知名国际期刊如 《IEEE Transactions on Neural Networks and Learning Systems》(TNNLS)、、《Information Sciences》、《IEEE Transactions on Industrial Informatics》(TII)、《Neurocomputing》等发表论文十余篇,申请发明专利多项。担任多个国际知名期刊如Information Sciences,Neurocomputing、Pattern Analysis and Applications、Neural Computing & Applications等的审稿人。当前的研究方向是显著性物体检测、语义分割、视频分析与合成、以及医学图像处理等。
赵靖亮,男,博士、博士后,现为澳门新葡萄新京app官网计算机学院青年百人讲师。2013年于河北大学物理学专业取得学士学位,2019年于北京理工大学光电学院取得博士学位,随后在南方医科大学生物医学工程学院开展博士后研究工作2年。目前,已在医学图像处理领域的顶级国际期刊《IEEE Transactions on Medical Imaging》和《IEEE Journal of Biomedical and Health Informatics》以及知名国际期刊上上发表论文多篇,相关理论成果已授权国家发明专利三项。博士期间提出的血管结构提取算法在MICCAI冠状动脉分割挑战赛中取得小组第一名。目前担任期刊IEEE Journal of Biomedical and Health Informatics的审稿人。当前从事的研究方向是主动脉夹层中心线提取、腔体分割、以及主动脉夹层智能诊疗应用研究。
团队成果
团队科研项目、部分科研论文、以及发明专利筛选展示如下。
近三年项目:
1. 国家重点研发计划,工业软件专项,2023YFB3308700,产业聚集区域业务资源服务工业软件平台,2023/12/01—2026/11/31,1000万,主持
2. 国家自然科学基金委员会, 重大研究计划, 92267107, 面向无人工厂智能制造的多智能体协同控制与决策, 2023-01-01 至 2025-12-31, 80万元, 在研, 参与;
3. 国家自然科学基金面上项目,61772143,脑老化动态复杂过程多模态知觉推理模型的研究,61万,2018/01- 2021/12,在研,主持;
4. 国家自然科学基金青年科学基金项目,62102098,基于多模态时间序列表征学习的肝癌早期风险预测算法研究,2022/01-2024/12,30万,在研,主持;
5. 国家自然科学基金青年科学基金项目,62102097,动态环境异构特征数据聚类分析研究,2022/01-2024/12,30万,在研,主持;
6. 广东省自然科学基金委,广东省基础与应用基础研究基金面上项目,非侵入式冠状动脉病变的智能定位与评估关键技术研究,2024/01—2026/12,15万,主持;
7. 广东省自然科学基金,面上项目,面向教育大数据聚类分析的表征学习研究,2023—2025,主持;
8. 广东省省级科技计划项目,2019A050510041, 心血管病辅助诊断和干预中多模态影像处理关键技术研究, 2020/01-2023/12,100万,在研,主持;
9. 广东省自然科学基金委,广东省基础与应用基础研究基金区域联合基金项目, 2022A1515140096, 多源异构热处理数据智能联网及其保护的关键技术研究, 2022/10—2025/09,30 万元,在研,校内主持;
10. 广东省自然科学基金项目,2022A1515011592,基于复杂异构特征医学数据挖掘的脓毒症智能预测方法研究,2022/01-2024/12,10万,在研,主持。
11. 广州市科技计划项目,201804010278, 基于数据挖掘技术的老年重症患者预后评估研究, 2018/04-2021/3,20万,在研,主持;
12. 广州市科技计划项目,基础与应用基础研究项目,基于分层聚类的多模态数据融合分析关键技术研究,2022—2024,主持;
13. 广州市科技局,广州市基础与应用基础研究项目,202201010266,肝活检图像的多类病变细胞弱监督自动检测算法研究,2022/04—2024/03,5万元,在研,主持;
科研论文(按时间倒序排列):
[1] Jiayu Ye, An Zeng*, Dan Pan, et al. MAD-Former: A Retrospective Interpretability Model for Alzheimer’s Disease Recognition based on Multi-patch Attention[J]. IEEE Journal of Biomedical and Health Informatics, 2024. (中科院二区Top,CCF推荐期刊,IF:7.7)
[2] Baoyao Yang*, PC Yuen, Yiqun Zhang, An Zeng, "Allosteric Feature Collaboration for Model-Heterogeneous Federated Learning," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024. (SCI一区,影响因子14.255,CCF-B)
[3] Xiaochen He, Baoyao Yang*, Fei Lyu, "MMS: Morphology-mixup Stylized Data Generation for Single Domain Generalization in Medical Image Segmentation," IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024. (CCF-B)
[4] Yuebin Xie, Xiaochen He, Baoyao Yang*, Fei Lyu, Siqi Liu, "CAM-Guided translation for unpaired weakly-supervised medical image segmentation," IEEE International Conference on Multimedia and Expo (ICME), 2024. (CCF-B)
[5] Pengkai Wang, Yiqun Zhang*, et. al., “Clustering by Learning the Ordinal Relationships of Qualitative Attribute Values”, Proceedings of the 2024 International Joint Conference on Neural Networks (IJCNN), pp. 1-8, Yokohama, Japan, June 30-July 5, 2024.
[6] Yi Li, Baoyao Yang, Dan Pan, An Zeng, Yang Yang, "Early diagnosis of Alzheimer's disease based on multimodal hypergraph attention network", International Conference on Multimedia and Expo, ICME, 2023. (CCF-B)
[7] Dan Pan, An Zeng*, Baoyao Yang*, Gangyong Lai, Bing Hu, Xiaowei Song, Tianzi Jiang, "Deep Learning for Brain MRI Confirms Patterned Pathological Progression in Alzheimer's Disease," Advanced Science, 2023. (SCI一区,影响因子17.521)
[8] Pan D, Luo G, Zeng A*, et al. Adaptive 3DCNN-Based Interpretable Ensemble Model for Early Diagnosis of Alzheimer’s Disease[J]. IEEE Transactions on Computational Social Systems, 2023, 11(1): 247-266. (中科院二区,CCF推荐期刊,IF:5.0)
[9] An Zeng ; Chunbiao Wu; Guisen Lin; Wen Xie; Jin Hong; Meiping Huang; Jian Zhuang; Shanshan Bi; Dan Pan; Najeeb Ullah; Kaleem Nawaz Khan ; ImageCAS: A large-scale dataset and benchmark for coronary artery segmentation based on computed tomography angiography images, Computerized Medical Imaging and Graphics, 2023, 109
[10] Yiqun Zhang and Yiu-ming Cheung*, “Graph-based Dissimilarity Measurement for Cluster Analysis of Any-Type-Attributed Data”, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Vol. 34, No. 9, pp. 6530-6544, 2023.
[11] Lang Zhao, Yiqun Zhang*, et. al, “Selecting Heterogeneous Features based on Unified Density-Guided Neighborhood Relation for Complex Biomedical Data Analysis”, Proceedings of the 2023 International Conference on Bioinformatics and Biomedicine (BIBM), pp. 1-8, Istanbul, Turkey, December 5-8, 2023.
[12] Zhipeng Zhang, Yiqun Zhang*, et. al, “Time-Series Data Imputation via Realistic Masking-Guided Tri-Attention Bi-GRU”, Proceedings of the 26th European Conference on Artificial Intelligence (ECAI), pp. 1-8, Krakow, Poland, October 2-4, 2023.
[13] Dan Pan, An Zeng*, Baoyao Yang, et al. Deep Learning for Brain MRI Confirms Patterned Pathological Progression in Alzheimer's Disease, Advanced Science, 2022(中科院一区Top,影响因子17.56)
[14] Pan D, Luo G, An Zeng *, et al. Adaptive 3DCNN-Based Interpretable Ensemble Model for Early Diagnosis of Alzheimer’s Disease[J]. IEEE Transactions on Computational Social Systems, 2022. (中科院二区,影响因子4.747)
[15] Baoyao Yang and Pong C. Yuen*, “Revealing Task-relevant Model Memorization for Source-Protected Unsupervised Domain Adaptation,” IEEE Transactions on Information Forensics and Security, 2022. (SCI一区,影响因子7.178,CCF-A)
[16] Yiqun Zhang, Yiu-ming Cheung* and An Zeng, Het2Hom: Representation of Heterogeneous Attributes into Homogeneous Concept Spaces for Categorical-and-Numerical-Attribute Data Clustering, the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI), 2022. (CCF-A)
[17] Yuzhu Ji, Haijun Zhang*, Feng Gao, Haofei Sun, Haokun Wei, Nan Wang, Biao Yang, “LGCNet: A Local-to-global Context-aware Feature Augmentation Network for Salient Object Detection”, Information Sciences, vol.584, pp.399-416, 2022.(SCI一区; 影响因子6.795;CCF-B)
[18] Baoyao Yang, Hao-wei Yeh, Tatsuya Harada, and Pong C. Yuen*, “Model-induced Generalization Error Bound for Information-theoretic Representation Learning in Source-data-free Unsupervised Domain Adaptation,” IEEE Transactions on Image Processing , Vol. 31, pp 419-431, 2022. (SCI一区,影响因子10.856;CCF-A)
[19] Grace Lai-Hung Wong*, Vicki Wing Ki Hui, Qingxiong Tan, Jingwen Xu, Hye Won, Terry Cheuk-Fung Yip, Baoyao Yang, Yee-Kit Tse, Chong Yin, Fei Lyu, "Novel machine learning models outperform risk scores in predicting hepatocellular carcinoma in patients with chronic viral hepatitis," JHEP Reports, 2022. (中科院SCI分区:1区;IF:8.3)
[20] Fei Lyu, Baoyao Yang, Andy J. Ma and Pong C. Yuen*, "A Segmentation-Assisted Model for Universal Lesion Detection with Partial Labels," International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI), 2021. (CCF-B)
[21] Hao-wei Yeh, Baoyao Yang, Pong C. Yuen and Tatsuya Harada*, "SoFA: Source-data-free Feature Alignment for Unsupervised Domain Adaptation," the IEEE Winter Conference on Applications of Computer Vision (WACV), 2021.
[22] Zhang Yiqun and Cheung Yiu-ming*, Learnable Weighting of Intra-attribute Distances for Categorical Data Clustering with Nominal and Ordinal Attributes, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021. (DOI: 10.1109/TPAMI.2021.3056510) (SCI一区,影响因子17.861,CCF-A)
[23] Yang Baoyao and Yuen Pong C.*, Learning Adaptive Geometry for Unsupervised Domain Adaptation, Pattern Recognition, 2021, (DOI: 10.1016/j.patcog.2020.107638) (SCI一区,影响因子7.196,CCF-B)
[24] Yuzhu Ji, Haijun Zhang*, Zhao Zhang and Ming Liu, “CNN-based Encoder-Decoder Networks for Salient Object Detection: A Comprehensive Review and Recent Advances”, Information Sciences, vol. 546, pp. 835-857, 2021.(SCI一区;影响因子6.795;WoS高被引论文;CCF-B)
[25] Yuzhu Ji, Haijun Zhang*, Zequn Jie, Lin Ma, and Q. M. Jonathan, Wu, “CASNet: A Cross attention Siamese Network for Video Salient Object Detection”, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 32(6), pp. 2676-2690, 2021.(SCI一区;影响因子10.451;CCF-B)
[26] An Zeng, Huabin Rong, Dan Pan *, Longfei Jia, Yiqun Zhang, Fengyi Zhao, Shaoliang Peng, for the Alzheimer's Disease Neuroimaging Initiative (ADNI), Discovery of Genetic Biomarkers for Alzheimer's Disease Using Adaptive Convolutional Neural Networks Ensemble and Genome-Wide Association Studies, Interdisciplinary Sciences: Computational Life Sciences 2021. 08.(中科院二区,IF:3.492)
[27] Jun Wang; Long Zhang; An Zeng; Dawen Xia; Jiantao Yu; Guoxian Yu. DeepIII: Predicting Isoform-isoform Interactions by Deep Neural Networks and Data Fusion. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2021. (中科院三区,IF:3.702;CCF-B)
[28] 潘丹, 邹超, 容华斌, 曾安. 基于遗传算法和三维卷积神经网络集成模型的阿尔茨海默症早期辅助诊断,生物医学工程学杂志, 2021, 38(1): 47-55. (EI源刊)
[29] Qingxiong Tan, Mang Ye, Baoyao Yang and Pong C. Yuen*, "DATA-GRU: Dual-Attention Time-Aware Gated Recurrent Unit for Irregular Multivariate Time Series," the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020. (CCF-A会议)
[30] Qingxiong Tan, Mang Ye, Andy Jinhua Ma, Baoyao Yang, Terry Cheuk-Fung Yip, Grace Lai-Hung Wong and Pong C Yuen*, "Explainable Uncertainty-Aware Convolutional Recurrent Neural Network for Irregular Medical Time Series," the IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020. (SCI一区,影响因子14.255,CCF-B)
[31] Grace Lai-Hung Wong*, Qingxiong Tan, Yee-Kit Tse, Baoyao Yang, Terry Cheuk-Fung Yip, Chong Yin, Vicki Wing Ki Hui, et al., "Machine Learning Models to Predict Hepatocellular Carcinoma in Patients with Chronic Viral Hepatitis – A Territory-wide Study from Hospital Authority Data Collaboration Lab (HADCL) in 2000-2017," Hepatology, 2020, 72:07030-5774. (SCI一区,影响因子14.679)
[32] Yang Baoyao, Ye Mang, Tan Qingxiong and Yuen Pong C.*, Cross-domain Missingness-aware Time Series Adaptation with Similarity Distillation in Medical Applications, IEEE Transactions on Cybernetics, 2020. (DOI: 10.1109/TCYB.2020.3011934) (SCI一区,影响因子11.079,CCF-B)
[33] Zhang Yiqun and Cheung Yiu-ming*, A New Distance Metric Exploiting Heterogeneous Inter-Attribute Relationship for Ordinal-and-Nominal-Attribute Data Clustering, IEEE Transactions on Cybernetics, 2020. (DOI: 10.1109/TCYB.2020.2983073) (SCI一区,影响因子11.079,CCF-B)
[34] Zhang Yiqun, Cheung Yiu-ming* and Tan Kay Chen, A Unified Entropy-Based Distance Metric for Ordinal-and-Nominal-Attribute Data Clustering, IEEE Transactions on Neural Networks and Learning Systems, 2020, 31(1): 39-52. (SCI一区,影响因子8.793,CCF-B)
[35] Pan Dan, Jia Longfei, Zeng An*, Huang Yin and Song Xiaowei, Early Detection of Alzheimer’s Disease using Magnetic Resonance Imaging: A Novel Approach Combining Convolutional Neural Networks and Ensemble Learning, Frontiers in Neuroscience, 2020.
[36] Zhang Yiqun and Cheung Yiu-ming*, An Ordinal Data Clustering Algorithm with Automated Distance Learning, the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020. (CCF-A)
[37] Jingliang Zhao, Jie Zhao, Shumao Pang, Qianjin Feng. Segmentation of the True Lumen of Aorta Dissection via Morphology-constrained Stepwise Deep Mesh Regression[J]. IEEE Transactions on Medical Imaging, 2022, 41(7): 1826-1836. (SCI一区, 影响因子11.037,医学图像处理Top,CCF-B)
[38] Jingliang Zhao, Qianjin Feng. Automatic Aortic Dissection Centerline Extraction via Morphology-guided CRN Tracker[J]. IEEE Journal of Biomedical and Health Informatics, 2021, 25(9): 3473-3485. (SCI一区, 影响因子7.021,医学图像处理Top,CCF-C)
[39] Jingliang Zhao, Danni Ai, Yang Yang, Hong Song, Yong Huang, Yongtian Wang, Jian Yang. Deep Feature Regression (DFR) for 3D Vessel Segmentation[J]. Physics in Medicine and Biology, 2019, 64(11): 115006. (SCI二区, 影响因子4.174)
[40] Jingliang Zhao, Jian Yang, Danni Ai, Hong Song, Yurong Jiang, Yong Huang, Luosha Zhang, Yongtian Wang. Automatic Retinal Vessel Segmentation using Multi-scale Superpixel Chain Tracking[J]. Digital Signal Processing, 2018, 81: 26-42. (SCI三区, 影响因子2.920)
[41] Yitian Zhao, Jingliang Zhao, Jian Yang, Yonghuai Liu, Yifan Zhao, Yalin Zheng, Likun Xia, Yongtian Wang. Saliency Driven Vasculature Segmentation With Infinite Perimeter Active Contour Model[J]. Neurocomputing, 2017, 259: 201-209. (SCI二区, 影响因子5.779,CCF-C)
发明专利:
1. 曾安; 刘淇乐; 潘丹; 徐小维; 吴春彪; 陈宇琛; 一种冠状动脉CT影像深度聚类和分割方法及系统, 2023-3-10, 中国, ZL202110443773.7(已授权)
2. 曾安; 米晨晰; 甘孟坤; 吴春彪; 潘丹; 一种基于多切片组合的冠状动脉分割方法和装置, 2023-1-24, 中国, ZL 202110644581.2(已授权)
3. 潘丹, 曾安, 杨宝瑶, 基于可解释集成3DCNN的神经影像学生物标志物的提取方法, 2022-11-22, ZL202210987102.5 (已授权)
4. 曾安; 陈国斌; 潘丹; 高征; 一种大脑影像智能分类方法、装置和设备, 2022-9-16, 中国, ZL202011569399.7(已授权)
5. 曾安, 谢锐伟, 潘丹,杨宝瑶, 张逸群, 一种心脏图像分割方法及系统, 2022-04-22, ZL202210030012.3(已授权)
6. 潘丹, 罗琳, 曾安, 廖清青, 杨宝瑶, 张逸群, 一种基于多头两级注意力的三维点云语义分割方法, 2022-11-04, ZL202210709918.8(已授权)
7. 曾安; 吴春彪; 潘丹; 徐小维; 刘淇乐; 陈宇琛 ; 一种冠状动脉分割方法、系统以及存储介质,2021-7-20, 中国, ZL202110509998.8(已授权)
8. 曾安; 王烈基; 潘丹; 一种肿瘤位置定位系统及相关装置, 2021-7-6, 中国,ZL201910554981.7(已授权)
9. 黄殷. 曾安. 潘丹. 用于识别医学图像的计算机系统[P]. 申请号: 2019-8-14, ZL201910661400.X. (已授权)
10. 曾安. 邹超. 潘丹. 医学图像分类装置及系统[P]. 申请号:201910376120.4, 2019-5-7. (已授权)
11. 曾安. 王烈基. 潘丹. 一种肿瘤位置定位系统及相关装置[P]. 申请号:201910554981.7, 2019-6-25. (已授权)
12. 曾安. 高征. 潘丹. 一种阿尔茨海默症分类预测方法及系统[P]. 申请号:201910824406.4, 2019-9-2. (已授权)
13. 曾安. 温创斐. 潘丹. 一种图像分类方法及系统[P]. 申请号:201910990121.8, 2019-10-17. (已授权)
14. 潘丹, 曾安,黄殷.一种阿尔茨海默症遗传生物标志物确定方法及系统;申请号:2019104502480;状态:(已授权)
15. 潘丹, 曾安,贾龙飞. 基于集成学习的阿尔茨海默症确定方法及系统;申请号:2018111672937;状态:(已授权)
16. 曾安. 王烈基. 潘丹.基于全卷积神经网络和互信息的医学图像配准方法及系统;申请号:2018111670382;状态:(已授权)
17. 潘丹. 曾安. 黎建忠. 基于支持向量机的阿尔茨海默症特征分类方法及系统;申请号:2017112860765;状态:(已授权)
18. 潘丹. 曾安. 黎建忠. 基于总体相关系数的阿尔茨海默症特征提取方法及系统;申请号:201711286045X;状态:(已授权)
19. 潘丹. 曾安. 黎建忠. 基于高斯过程分类的阿尔茨海默症分类方法、系统及装置;申请号:2017112841938;状态:(已授权)