1.           Jiayue Zhang, Yiheng Liu, Wenqi Cai, Yali Peng, Senqing Qi, Taotao Long, and Bao Ge, Investigation of the effectiveness of applying ChatGPT in Dialogic Teaching Using Electroencephalography. arXiv preprint arXiv:2403.16687, 2024.

2.           Jiaqi Wang, Zihao Wu, Yiwei Li, Hanqi Jiang, Peng Shu, Enze Shi, Huawen Hu, Chong Ma, Yiheng Liu, and Xuhui Wang, Large language models for robotics: Opportunities, challenges, and perspectives. arXiv preprint arXiv:2401.04334, 2024.

3.           Jiaqi Wang, Hanqi Jiang, Yiheng Liu, Chong Ma, Xu Zhang, Yi Pan, Mengyuan Liu, Peiran Gu, Sichen Xia, and Wenjun Li, A Comprehensive Review of Multimodal Large Language Models: Performance and Challenges Across Different Tasks. arXiv preprint arXiv:2408.01319, 2024.

4.           Saed Rezayi, Zhengliang Liu, Zihao Wu, Chandra Dhakal, Bao Ge, Haixing Dai, Gengchen Mai, Ninghao Liu, Chen Zhen, and Tianming Liu, Exploring new frontiers in agricultural nlp: Investigating the potential of large language models for food applications. IEEE Transactions on Big Data, 2024.

5.           Ning Qiang, Qinglin Dong, Heng Huang, Han Wang, Shijie Zhao, Xintao Hu, Qing Li, Wei Zhang, Yiheng Liu, and Mengshen He, Deep learning in functional brain mapping and associated applications, in Deep Learning for Medical Image Analysis. 2024, Academic Press. p. 395-423.

6.           Yiheng Liu, Hao He, Tianle Han, Xu Zhang, Mengyuan Liu, Jiaming Tian, Yutong Zhang, Jiaqi Wang, Xiaohui Gao, and Tianyang Zhong, Understanding llms: A comprehensive overview from training to inference. arXiv preprint arXiv:2401.02038, 2024.

7.           Yiheng Liu, Enjie Ge, Zili Kang, Ning Qiang, Tianming Liu, and Bao Ge, Spatial-temporal convolutional attention for discovering and characterizing functional brain networks in task fMRI. NeuroImage, 2024. 287: p. 120519.

8.           Yiheng Liu, Enjie Ge, Zili Kang, Ning Qiang, Tianming Liu, and Bao Ge, Spatial-temporal convolutional attention for discovering and characterizing functional brain networks in task fMRI. NeuroImage, 2024: p. 120519.

9.           Yiheng Liu, Enjie Ge, Mengshen He, Zhengliang Liu, Shijie Zhao, Xintao Hu, Ning Qiang, Dajiang Zhu, Tianming Liu, and Bao Ge, Mapping dynamic spatial patterns of brain function with spatial-wise attention. Journal of Neural Engineering, 2024.

10.         Yiheng Liu, Enjie Ge, Mengshen He, Zhengliang Liu, Shijie Zhao, Xintao Hu, Ning Qiang, Dajiang Zhu, Tianming Liu, and Bao Ge, Mapping dynamic spatial patterns of brain function with spatial-wise attention. Journal of Neural Engineering, 2024. 21(2): p. 026005.

11.         Wenjun Li, Ying Cai, Ziyang Wu, Wenyi Zhang, Yifan Chen, Rundong Qi, Mengqi Dong, Peigen Chen, Xiao Dong, and Fenghao Shi, A Survey of Foundation Models for Music Understanding. arXiv preprint arXiv:2409.09601, 2024.

12.         Tianle Han, Yifan Lv, Mengshen He, Yiheng

Liu Liu, Tianming, and Bao Ge, Brain Cortical Surface Can Predict Fiber Trajectories, in ISBI. 2024: Athens.

13.         Tianle Han, Yifan Lv, Mengshen He, Yiheng Liu, Tianming Liu, and Bao Ge. Brain Cortical Surface Can Predict Fiber Trajectories. in 2024 IEEE International Symposium on Biomedical Imaging (ISBI). 2024. IEEE.

14.         Zhenwei Wang, Mengshen He, Yifan Lv, Enjie Ge, Shu Zhang, Ning Qiang, Tianming Liu, Fan Zhang, Xiang Li, and Bao Ge, Accurate corresponding fiber tract segmentation via FiberGeoMap learner with application to autism. Cerebral Cortex, 2023: p. bhad125.

15.         Jiaqi Wang, Enze Shi, Sigang Yu, Zihao Wu, Chong Ma, Haixing Dai, Qiushi Yang, Yanqing Kang, Jinru Wu, and Huawen Hu, Prompt engineering for healthcare: Methodologies and applications. arXiv preprint arXiv:2304.14670, 2023.

16.         Jiaqi Wang, Zhengliang Liu, Lin Zhao, Zihao Wu, Chong Ma, Sigang Yu, Haixing Dai, Qiushi Yang, Yiheng Liu, and Songyao Zhang, Review of large vision models and visual prompt engineering. Meta-Radiology, 2023: p. 100047.

17.         Saed Rezayi, Zhengliang Liu, Zihao Wu, Chandra Dhakal, Bao Ge, Haixing Dai, Gengchen Mai, Ninghao Liu, Chen Zhen, and Tianming Liu, Exploring New Frontiers in Agricultural NLP: Investigating the Potential of Large Language Models for Food Applications. arXiv preprint arXiv:2306.11892, 2023.

18.         Ning Qiang, Jie Gao, Qinglin Dong, Huiji Yue, Hongtao Liang, Lili Liu, Jingjing Yu, Jing Hu, Shu Zhang, and Bao Ge, Functional brain network identification and fMRI augmentation using a VAE-GAN framework. Computers in Biology and Medicine, 2023. 165: p. 107395.

19.         Ning Qiang, Jie Gao, Qinglin Dong, Jin Li, Shu Zhang, Hongtao Liang, Yifei Sun, Bao Ge, Zhengliang Liu, and Zihao Wu, A deep learning method for autism spectrum disorder identification based on interactions of hierarchical brain networks. Behavioural Brain Research, 2023. 452: p. 114603.

20.         Yifan Lv, Zili Kang, Tianle Han, Mengshen He, Ruhai Du, Tuo Zhang, Tianming Liu, and Bao Ge, Cerebral cortical regions always connect with each other via the shortest paths. Cerebral Cortex, 2023: p. bhad197.

21.         Zhengliang Liu, Tianyang Zhong, Yiwei Li, Yutong Zhang, Yi Pan, Zihao Zhao, Peixin Dong, Chao Cao, Yuxiao Liu, and Peng Shu, Evaluating large language models for radiology natural language processing. arXiv preprint arXiv:2307.13693, 2023.

22.         Zhengliang Liu, Hanqi Jiang, Tianyang Zhong, Zihao Wu, Chong Ma, Yiwei Li, Xiaowei Yu, Yutong Zhang, Yi Pan, and Peng Shu, Holistic evaluation of gpt-4v for biomedical imaging. arXiv preprint arXiv:2312.05256, 2023.

23.        Yiheng Liu, Tianle Han, Siyuan Ma, Jiayue Zhang, Yuanyuan Yang, Jiaming Tian, Hao He, Antong Li, Mengshen He, and Zhengliang Liu, Summary of chatgpt-related research and perspective towards the future of large language models. Meta-Radiology, 2023: p. 100017.

24.         Yiheng Liu, Enjie Ge, Ning Qiang, Tianming Liu, and Bao Ge. Spatial-temporal convolutional attention for mapping functional brain networks. in 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI). 2023. IEEE.

25.         Zili Kang, Yifan Lv, Mengshen He, Yiheng Liu, Tianming Liu, and Bao Ge. Brain Surface Can Predict Fiber Connections. in 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI). 2023. IEEE.

26.         Xinlei Jia, Yali Peng, Bao Ge, Jun Li, Shigang Liu, and Wenan Wang, A multi-scale dilated residual convolution network for image denoising. Neural Processing Letters, 2023. 55(2): p. 1231-1246.

27.         Mengshen He, Xiangyu Hou, Enjie Ge, Zhenwei Wang, Zili Kang, Ning Qiang, Xin Zhang, and Bao Ge, Multi-head attention-based masked sequence model for mapping functional brain networks. Frontiers in Neuroscience, 2023. 17: p. 1183145.

28.         Zhenwei Wang, Yifan Lv, Mengshen He, Enjie Ge, Ning Qiang, and Bao Ge. Accurate Corresponding Fiber Tract Segmentation via FiberGeoMap Learner. in International Conference on Medical Image Computing and Computer-Assisted Intervention. 2022. Springer Nature Switzerland Cham.

29.         Saed Rezayi, Zhengliang Liu, Zihao Wu, Chandra Dhakal, Bao Ge, Chen Zhen, Tianming Liu, and Sheng Li. Agribert: knowledge-infused agricultural language models for matching food and nutrition. in Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 2022.

30.         Ning Qiang, Qinglin Dong, Hongtao Liang, Jin Li, Shu Zhang, Cheng Zhang, Bao Ge, Yifei Sun, Jie Gao, and Tianming Liu, Learning brain representation using recurrent Wasserstein generative adversarial net. Computer Methods and Programs in Biomedicine, 2022. 223: p. 106979.

31.         Ning Qiang, Qinglin Dong, Hongtao Liang, Bao Ge, Shu Zhang, Cheng Zhang, Jie Gao, and Yifei Sun, A novel ADHD classification method based on resting state temporal templates (RSTT) using spatiotemporal attention auto-encoder. Neural Computing and Applications, 2022. 34(10): p. 7815-7833.

32.         Zhengliang Liu, Mengshen He, Zuowei Jiang, Zihao Wu, Haixing Dai, Lian Zhang, Siyi Luo, Tianle Han, Xiang Li, and Xi Jiang, Survey on natural language processing in medical image analysis. Zhong nan da xue xue bao. Yi xue ban= Journal of Central South University. Medical Sciences, 2022. 47(8): p. 981-993.

33.         Yiheng Liu, Enjie Ge, Mengshen He, Zhengliang Liu, Shijie Zhao, Xintao Hu, Dajiang Zhu, Tianming Liu, and Bao Ge, Discovering Dynamic Functional Brain Networks via Spatial and Channel-wise Attention. arXiv preprint arXiv:2205.09576, 2022.

34.         Xinlei Jia, Yali Peng, Jun Li, Yunhong Xin, Bao Ge, and Shigang Liu, Pyramid dilated convolutional neural network for image denoising. Journal of Electronic Imaging, 2022. 31(2): p. 023024-023024.

35.         Mengshen He、Xiangyu Hou、Zhenwei Wang、Zili Kang、Xin Zhang、Ning Qiang、Bao Ge, Multi-head Attention-Based Masked Sequence Model for Mapping Functional Brain Networks. Medical Image Computing and Computer Assisted Intervention – MICCAI 2022, 2022.

36.         Ning Qiang, Qinglin Dong, Hongtao Liang, Bao Ge, Shu Zhang, Yifei Sun, Cheng Zhang, Wei Zhang, Jie Gao, and Tianming Liu, Modeling and augmenting of fMRI data using deep recurrent variational auto-encoder. Journal of neural engineering, 2021. 18(4): p. 0460b6.

37.         Xinlei Jia, Yali Peng, Jun Li, Bao Ge, Yunhong Xin, and Shigang Liu, Dual-complementary convolution network for remote-sensing image denoising. IEEE Geoscience and Remote Sensing Letters, 2021. 19: p. 1-5.

38.         Huan Wang, Qinglin Dong, Ning Qiang, Xin Zhang, Tianming Liu, and Bao Ge. Task fMRI guided Fiber clustering via a deep clustering method. in 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). 2020. IEEE.

39.         Ning Qiang, Bao Ge, Qinglin Dong, Fangfei Ge, and Tianming Liu. Neural architecture search for optimizing deep belief network models of fMRI data. in Multiscale Multimodal Medical Imaging: First International Workshop, MMMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings 1. 2020. Springer.

40.         Ning Qiang, Qinglin Dong, Wei Zhang, Bao Ge, Fangfei Ge, Hongtao Liang, Yifei Sun, Jie Gao, and Tianming Liu, Modeling task-based fMRI data via deep belief network with neural architecture search. Computerized Medical Imaging and Graphics, 2020. 83: p. 101747.

41.         Ning Qiang, Qinglin Dong, Yifei Sun, Bao Ge, and Tianming Liu. deep variational autoencoder for modeling functional brain networks and ADHD identification. in 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). 2020. IEEE.

42.         Ning Qiang, Qinglin Dong, Fangfei Ge, Hongtao Liang, Bao Ge, Shu Zhang, Yifei Sun, Jie Gao, and Tianming Liu, Deep variational autoencoder for mapping functional brain networks. IEEE Transactions on Cognitive and Developmental Systems, 2020. 13(4): p. 841-852.

43.         Bao Ge, Huan Wang, Panpan Wang, Yin Tian, Xin Zhang, and Tianming Liu, Discovering and characterizing dynamic functional brain networks in task FMRI. Brain Imaging and Behavior, 2020. 14: p. 1660-1673.

44.         Bao Ge, Xiang Li, Xi Jiang, Yifei Sun, and Tianming Liu, A dictionary learning approach for signal sampling in task-based fMRI for reduction of big data. Frontiers in Neuroinformatics, 2018. 12: p. 17.

45.         Yin Tian, Ke Yao, Pei-Qi Wang, and Bao Ge. Flipped Classroom in Computer Networks. in Humanity and Social Science: Proceedings of the International Conference on Humanity and Social Science (ICHSS2016). 2017. World Scientific.

46.         Yu Zhao, Hanbo Chen, Yujie Li, Jinglei Lv, Xi Jiang, Fangfei Ge, Tuo Zhang, Shu Zhang, Bao Ge, and Cheng Lyu, Connectome-scale group-wise consistent resting-state network analysis in autism spectrum disorder. NeuroImage: Clinical, 2016. 12: p. 23-33.

47.         Shijie Zhao, Junwei Han, Xi Jiang, Xintao Hu, Jinglei Lv, Shu Zhang, Bao Ge, Lei Guo, and Tianming Liu. Exploring auditory network composition during free listening to audio excerpts via group-wise sparse representation. in 2016 IEEE International Conference on Multimedia and Expo (ICME). 2016. IEEE.

48.         Bao Ge, Milad Makkie, Jin Wang, Shijie Zhao, Xi Jiang, Xiang Li, Jinglei Lv, Shu Zhang, Wei Zhang, and Junwei Han, Signal sampling for efficient sparse representation of resting state FMRI data. Brain imaging and behavior, 2016. 10: p. 1206-1222.

49.         Shijie Zhao, Junwei Han, Jinglei Lv, Xi Jiang, Xintao Hu, Yu Zhao, Bao Ge, Lei Guo, and Tianming Liu, Supervised dictionary learning for inferring concurrent brain networks. IEEE transactions on medical imaging, 2015. 34(10): p. 2036-2045.

50.         Tuo Zhang, Hanbo Chen, Xi Jiang, Bao Ge, Lei Guo, and Tianming Liu. Group-wise consistent sulcal fundi segmentation based on DMRI-derived ODF features. in 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI). 2015. IEEE.

51.         Shu Zhang, Xiang Li, Jinglei Lv, Xi Jiang, Bao Ge, Lei Guo, and Tianming Liu. Characterizing and differentiating task-based and resting state FMRI signals via two-stage dictionary learning. in 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI). 2015. IEEE.

52.         Milad Makkie, Shijie Zhao, Xi Jiang, Jinglei Lv, Yu Zhao, Bao Ge, Xiang Li, Junwei Han, and Tianming Liu, HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI). Brain informatics, 2015. 2: p. 225-238.

53.         Ke Jing, Tuo Zhang, Jianfeng Lu, Hanbo Chen, Xi Jiang, Lei Guo, Longchuan Li, Xiaoping Hu, Jinglei Lv, and Bao Ge. Multiscale and multimodal fusion of tract-tracing and DTI-derived fibers in macaque brains. in 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI). 2015. IEEE.

54.        Juanli Han, Gangqiang Zhu, Mirabbos Hojamberdiev, Jianhong Peng, Xi Zhang, Yun Liu, Bao Ge, and Peng Liu, Rapid adsorption and photocatalytic activity for Rhodamine B and Cr (VI) by ultrathin BiOI nanosheets with highly exposed {001} facets. New Journal of Chemistry, 2015. 39(3): p. 1874-1882.

55.         Fangfei Ge, Jinglei Lv, Xintao Hu, Bao Ge, Lei Guo, Junwei Han, and Tianming Liu. Deriving ADHD biomarkers with sparse coding based network analysis. in 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI). 2015. IEEE.

56.         Bao Ge, Yin Tian, Xintao Hu, Hanbo Chen, Dajiang Zhu, Tuo Zhang, Junwei Han, Lei Guo, and Tianming Liu, Construction of multi-scale consistent brain networks: methods and applications. PloS one, 2015. 10(4): p. e0118175.

57.         Tuo Zhang, Dajiang Zhu, Xi Jiang, Bao Ge, Xintao Hu, Junwei Han, Lei Guo, and Tianming Liu, Predicting cortical ROIs via joint modeling of anatomical and connectional profiles. Medical image analysis, 2013. 17(6): p. 601-615.

58.         Bao Ge, Lei Guo, Dajiang Zhu, Tuo Zhang, Xintao Hu, Junwei Han, and Tianming Liu. Construction of multi-scale common brain networks based on DICCCOL. in Information Processing in Medical Imaging: 23rd International Conference, IPMI 2013, Asilomar, CA, USA, June 28–July 3, 2013. Proceedings 23. 2013. Springer.

59.         Bao Ge, Lei Guo, Tuo Zhang, Dajiang Zhu, Xintao Hu, Junwei Han, and Tianming Liu. Construction of multi-scale brain networks via DICCCOL landmarks. in 2013 IEEE 10th International Symposium on Biomedical Imaging. 2013. IEEE.

60.         Bao Ge, Lei Guo, Tuo Zhang, Xintao Hu, Junwei Han, and Tianming Liu, Resting state fMRI-guided fiber clustering: methods and applications. Neuroinformatics, 2013. 11: p. 119-133.

61.         Bao Ge, Lei Guo, Tuo Zhang, Dajiang Zhu, Kaiming Li, Xintao Hu, Junwei Han, and Tianming Liu. Group-wise consistent fiber clustering based on multimodal connectional and functional profiles. in Medical Image Computing and Computer-Assisted Intervention–MICCAI 2012: 15th International Conference, Nice, France, October 1-5, 2012, Proceedings, Part III 15. 2012. Springer Berlin Heidelberg.

62.         Bao Ge, Lei Guo, Jinglei Lv, Xintao Hu, Junwei Han, Tuo Zhang, and Tianming Liu. Resting state fMRI-guided fiber clustering. in Medical Image Computing and Computer-Assisted Intervention–MICCAI 2011: 14th International Conference, Toronto, Canada, September 18-22, 2011, Proceedings, Part II 14. 2011. Springer.

63.         Bao Ge, Lei Guo, Kaiming Li, Hai Li, Carlos Faraco, Qun Zhao, Stephen Miller, and Tianming Liu. Automatic clustering of white matter fibers based on symbolic sequence analysis. in Medical Imaging 2010: Image Processing. 2010. SPIE.