Keqi Han

According to our database, Keqi Han authored at least 13 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

EHRBench: An Automated and Reliable EHR-based Benchmark for Clinical Decision Making with LLMs.

Yuzhang Xie, Keqi Han, Yunpeng Xiao, Hejie Cui, Guanchen Wu, Ziyang Zhang, Kai Shu, Jiaying Lu, Xiao Hu, Carl Yang

CoRR, May, 2026

Towards a Virtual Neuroscientist: Autonomous Neuroimaging Analysis via Multi-Agent Collaboration.

Keqi Han, Songlin Zhao, Yao Su, Xiang Li, Yixuan Yuan, Lifang He, Carl Yang

CoRR, May, 2026

A Benchmark Analysis of Graph and Non-Graph Methods for Caenorhabditis Elegans Neuron Classification.

Jingqi Lu, Keqi Han, Yun Wang, Lu Mi, Carl Yang

Proceedings of the 23rd IEEE International Symposium on Biomedical Imaging, 2026

Atlas-Free Functional Brain Connectome Analysis Via Task-Driven Parcellation.

Keqi Han, Yao Su, Songlin Zhao, Charles Gillespie, Boadie Dunlop, Daniel Barron, Randy Hirschtick, Liang Zhan, Lifang He, Xiang Li, Carl Yang

Proceedings of the 23rd IEEE International Symposium on Biomedical Imaging, 2026

2025

Rethinking Functional Brain Connectome Analysis: Do Graph Deep Learning Models Help?

Keqi Han, Yao Su, Lifang He, Liang Zhan, Sergey M. Plis, Vince D. Calhoun, Carl Yang

CoRR, January, 2025

Causal Brain Connectivity: Integrating Granger Directed Graphs in fMRI Analysis.

Tianyi Zhang, Keqi Han, Jiawei Nie, Chenyu You, Sanne J. H. van Rooij, Jennifer S. Stevens, Boadie Dunlop, Charles Gillespie, Carl Yang

Proceedings of the Artificial Intelligence in Medicine - 23rd International Conference, 2025

End-to-End Deep Learning for Structural Brain Imaging: A Unified Framework.

Yao Su, Keqi Han, Mingjie Zeng, Lichao Sun, Liang Zhan, Carl Yang, Lifang He, Xiangnan Kong

Proceedings of the 2025 AAAI Spring Symposium Series, 2025

2024

Multi-task Learning for Brain Network Analysis in the ABCD Study.

Xuan Kan, Hejie Cui, Keqi Han, Ying Guo, Carl Yang

Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics, 2024

Learning Diffusions under Uncertainty.

Hao Huang, Qian Yan, Keqi Han, Ting Gan, Jiawei Jiang, Quanqing Xu, Chuanhui Yang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Multi-aspect Diffusion Network Inference.

Hao Huang, Keqi Han, Beicheng Xu, Ting Gan

Proceedings of the ACM Web Conference 2023, 2023

2022

Reconstructing Diffusion Networks from Incomplete Data.

Hao Huang, Keqi Han, Beicheng Xu, Ting Gan

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021

Diffusion Network Inference from Partial Observations.

Ting Gan, Keqi Han, Hao Huang, Shi Ying, Yunjun Gao, Zongpeng Li

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Statistical Estimation of Diffusion Network Topologies.

Keqi Han, Yuan Tian, Yunjia Zhang, Ling Han, Hao Huang, Yunjun Gao

Proceedings of the 36th IEEE International Conference on Data Engineering, 2020