丛山｜哈尔滨工程大学｜学者主页

期刊论文

2026

scURL: Uncertainty-Sharpened Representation Learning for Single-cell Multi-omics Clustering.

Hong-Wei Liu, Dong-Hui Yu, Wei Li, Tong Zhang, Ching-Yu Cheng, Hua-Zhu Fu, Hong Liang, Shan Cong, Xiao-Hui Yao

Bioinformatics

2026

BriGHT: transcriptome-regularized multimodal neuroimaging for brain disorder prediction

Zhou-Jie Fan, Hao-Ran Luo, Hui Zhou, Hao Meng, Hong Liang, Zheng Wang, Hua-Zhu Fu, Ching-Yu Cheng, Shan Cong, Xiao-Hui Yao

Bioinformatics

DOI

2026

Convergence of spatially dispersed atrophy into functional networks in temporal lobe epilepsy: glial-immune signature associated with circuit dysfunction and treatment response.

Yi-Chun Huang, Zi-Rong Chen, Miao Zhang, Yu-Ting Sun, Qun-Bo Jia, Hong-Yi Li, Rong-Hui Ju, Shan Cong, Xiao-Hui Yao, Jia-Hao Huang, Yuan-Jing Feng, Biao Li, Jin-Ou Zheng, Zheng Wang

Neurobiology of Disease

DOI

2026

TNM-Accountable Whole-Body 3-Dimensional Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Report Drafting in Lung Cancer Cohorts via Structured Impressions and Organ-wise Exemplar Synthesis

Han Wang, Xingyu Xie, Entao Liu, Yunlong Gao, Xiaorui Wu, Shan Cong, Jidong Han, Na Zhang, Hai-Rong Zheng, Dong Liang, Xiao-Hui Yao, Lei Jiang, Zhan-Li Hu

Research

DOI

2026

CAMM: Confidence-Aligned Multiview Multimodal Fusion for Brain Disorders Prediction With Imaging Transcriptomics.

Hao-Ran Luo, Zhou-Jie Fan, Wei Li, Hong Liang, Chen Zhang, Xiaoyong Wei, Zheng Wang, Shan Cong, Xiao-Hui Yao

IEEE journal of biomedical and health informatics

DOI

2025

MedScaleRE-PF: a prompt-based framework with retrieval-augmented generation, chain-of-thought, and self-verification for scale-specific relation extraction in Chinese medical literature

Zhenli Chen, Jie Hao, Haixia Sun, Liang Zhao, Jiao Li, Qing Qian, Qinglong Peng, Xuwen Wang, Shan Cong, Liu Shen, Zhen Guo, Siyue Pu, Yan Lin

Information Processing & Management，Vol. 62, No. 6

DOI

2025

Prompt Framework for Extracting Scale-Related Knowledge Entities from Chinese Medical Literature: Development and Evaluation Study

Jie Hao, Zhenli Chen, Qinglong Peng, Liang Zhao, Wanqing Zhao, Shan Cong, Junlian Li, Jiao Li, Qing Qian, Haixia Sun

Journal Of Medical Internet Research，Vol. 27

DOI

2025

DC-GCE Loss: Robust Medical Image Classification Under Label Noise

Chao-Yi Ke, Yuhang Sun, Weihao Xia, Xiang-Yu Ma, Xiao-Hui Yao, Shan Cong, James Lo, Hua-Chuan Wang

IEEE International Conference on Bioinformatics and Biomedicine

DOI

2025

A Module-Level Polygenic Risk Score-Based NetWAS Framework for Identifying AD Genetic Modules Mediated by Amygdala: An ADNI Study

Haoran Luo, Shaoheng Fan, Hongwei Liu, Wei Li, Zhoujie Fan, Xuancheng Zhu, Chen Zhang, Hong Liang, Shan Cong, Xiaohui Yao

International Journal of Molecular Sciences

DOI

2024

Trustworthy Enhanced Multi-view Multi-modal Alzheimer’s Disease Prediction with Brain-wide Imaging Transcriptomics Data

Shan Cong, Zhou-Jie Fan, Hong-Wei Liu, Ying-Han Zhang, Xin Wang, Hao-Ran Luo, Xiao-Hui Yao

IEEE International Conference on Bioinformatics and Biomedicine

DOI

2024

Comprehensive review of Transformer‐based models in neuroscience, neurology, and psychiatry

Shan Cong, Hang Wang, Yang Zhou, Zheng Wang, Xiao-Hui Yao, Chunsheng Yang

Brain‐X

DOI

2024

DDASR: Domain-Distance Adapted Super-Resolution Reconstruction of MR Brain Images

Shan Cong, K. Cui, Yu-Zun Yang, Yang Zhou, Xin-Xin Wang, Hao-Ran Luo, Yichi Zhang, Xiao-Hui Yao

IEEE International Conference on Systems, Man and Cybernetics

DOI

2024

TEMINET: A Co-Informative and Trustworthy Multi-Omics Integration Network for Diagnostic Prediction

Haoran Luo, Hong Liang, Hongwei Liu, Zhoujie Fan, Yanhui Wei, Xiaohui Yao, Shan Cong

International Journal of Molecular Sciences

DOI

2024

Multimodal radiomics-based methods using deep learning for prediction of brain metastasis in non-small cell lung cancer with 18F-FDG PET/CT images

Yuan Zhu, Shan Cong, Qiyang Zhang, Zhenxing Huang, Xiaohui Yao, You Cheng, Dong Liang, Zhanli Hu, Dan Shao

Biomedical Physics & Engineering Express

DOI

2024

Fusion of shallow and deep features from 18F-FDG PET/CT for predicting EGFR-sensitizing mutations in non-small cell lung cancer

Xiaohui Yao, Yuan Zhu, Zhenxing Huang, Yue Wang, Shan Cong, Liwen Wan, Ruodai Wu, Long Chen, Zhanli Hu

Quantitative Imaging in Medicine and Surgery

DOI

2023

“人工智能+脑科学”交叉学科教学模式探索

姚晓辉，苑硕，鲍佩华，梁洪，李妍虹，李金，何忠杰，唐墨，丛山

《创新创业理论研究与实践》

2023

MOCAT: multi-omics integration with auxiliary classifiers enhanced autoencoder

Xiao-Hui Yao, Xiao-Han Jiang, Haoran Luo, Hong Liang, Xiu-Fen Ye, Yanhui Wei, Shan Cong

BioData Mining

DOI

2023

GREMI: an Explainable Multi-omics Integration Framework for Enhanced Disease Prediction and Module Identification

Hong Liang, Haoran Luo, Z. Sang, M. Jia, Xiao-Han Jiang, Zheng Wang, Shan Cong, Xiao-Hui Yao

bioRxiv

DOI

2023

MR Image Harmonization with Transformer

Dong Han, Rui Yu, Shi-Peng Li, Junchang Wang, Yu-Zun Yang, Zhixun Zhao, Yi-Ming Wei, Shan Cong

2023 IEEE International Conference on Mechatronics and Automation (ICMA)

DOI

2023

Adversarially Trained Persistent Homology Based Graph Convolutional Network for Disease Identification Using Brain Connectivity

Chenyuan Bian, Nan L. Xia, Anmu Xie, Shan Cong, Qian Dong

IEEE Transactions on Medical Imaging

DOI

2022

“人工智能+脑科学”交叉学科人才培养框架探索

姚晓辉，苑硕，鲍佩华，丛山

《教育信息化论坛》

预印本

2023

Integration of tissue-specific multi-omics data implicates brain targets for complex neuropsychiatric traits

Shan Cong, Zhiling Sang, Luolong Cao, Jun-Bo Yuan, Yanhong Li, Hong Liang, Xiaohui Yao

medRxiv

DOI

2018

Image Registration and Predictive Modeling: Learning the Metric on the Space of Diffeomorphisms

Ayagoz Mussabayeva, Alexey Kroshnin, Anvar Kurmukov, Yulia Dodonova, Li Shen, Shan Cong, Lei Wang, Boris A. Gutman

arXiv preprint

2018

Deep Learning for Quality Control of Subcortical Brain 3D Shape Models

Dmitry Petrov, Boris A. Gutman Egor Kuznetsov, Theo G. M. van Erp, Jessica A. Turner, Lianne Schmaal, Dick Veltman, Lei Wang, Kathryn Alpert, Dmitry Isaev, Artemis Zavaliangos-Petropulu, Christopher R. K. Ching, Vince Calhoun, David Glahn, Theodore D. Satterthwaite, Ole Andreas Andreassen, Stefan Borgwardt, Fleur Howells, Nynke Groenewold, Aristotle Voineskos, Joaquim Radua, Steven G. Potkin, Benedicto Crespo-Facorro, Diana Tordesillas-Gutierrez, Li Shen, Irina Lebedeva, Gianfranco Spalletta, Gary Donohoe, Peter Kochunov, Pedro G. P. Rosa, Anthony James, Udo Dannlowski, Bernhard T. Baune, Andre Aleman, Ian H. Gotlib, Henrik Walter, Martin Walter, Jair C. Soares, Stefan Ehrlich, Ruben C. Gur, N. Trung Doan, Ingrid Agartz, Lars T. Westlye, Fabienne Harrisberger, Anita Riecher-Rossler, Anne Uhlmann, Dan J. Stein, Erin W. Dickie, Edith Pomarol-Clotet, Paola Fuentes-Claramonte, Erick Jorge Canales-Rodriguez, Raymond Salvador, Alexander J. Huang, Roberto Roiz-Santianez, Shan Cong, Alexander Tomyshev, Fabrizio Piras, Daniela Vecchio, Nerisa Banaj, Valentina Ciullo, Elliot Hong, Geraldo Busatto, Marcus V. Zanetti, Mauricio H. Serpa, Simon Cervenka, Sinead Kelly, Dominik Grotegerd, Matthew D. Sacchet, Ilya M. Veer, Meng Li, Mon-Ju Wu, Benson Irungu, Esther Walton, Paul M. Thompson

arXiv preprint

2017

Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging

Dmitry Petrov, Boris A. Gutman, Shih-Hua, Yu, Theo G. M. van Erp, Jessica A. Turner, Lianne Schmaal, Dick Veltman, Lei Wang, Kathryn Alpert, Dmitry Isaev, Artemis Zavaliangos-Petropulu, Christopher R. K. Ching, Vince Calhoun, David Glahn, Theodore D. Satterthwaite, Ole Andreas Andreasen, Stefan Borgwardt, Fleur Howells, Nynke Groenewold, Aristotle Voineskos, Joaquim Radua, Steven G. Potkin, Benedicto Crespo-Facorro, Diana Tordesillas-Gutierrez, Li Shen, Irina Lebedeva, Gianfranco Spalletta, Gary Donohoe, Peter Kochunov, Pedro G. P. Rosa, Anthony James, Udo Dannlowski, Bernhard T. Baune, Andre Aleman, Ian H. Gotlib, Henrik Walter, Martin Walter, Jair C. Soares, Stefan Ehrlich, Ruben C. Gur, N. Trung Doan, Ingrid Agartz, Lars T. Westlye, Fabienne Harrisberger, Anita Riecher-Rossler, Anne Uhlmann, Dan J. Stein, Erin W. Dickie, Edith Pomarol-Clotet, Paola Fuentes-Claramonte, Erick Jorge Canales-Rodriguez, Raymond Salvador, Alexander J. Huang, Roberto Roiz-Santianez, Shan Cong, Alexander Tomyshev, Fabrizio Piras, Daniela Vecchio, Nerisa Banaj, Valentina Ciullo, Elliot Hong, Geraldo Busatto, Marcus V. Zanetti, Mauricio H. Serpa, Simon Cervenka, Sinead Kelly, Dominik Grotegerd, Matthew D. Sacchet, Ilya M. Veer, Meng Li, Mon-Ju Wu, Benson Irungu, Esther Walton, Paul M. Thompson

arXiv preprint

丛山

精选作品

期刊论文

scURL: Uncertainty-Sharpened Representation Learning for Single-cell Multi-omics Clustering.

BriGHT: transcriptome-regularized multimodal neuroimaging for brain disorder prediction

Convergence of spatially dispersed atrophy into functional networks in temporal lobe epilepsy: glial-immune signature associated with circuit dysfunction and treatment response.

TNM-Accountable Whole-Body 3-Dimensional Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Report Drafting in Lung Cancer Cohorts via Structured Impressions and Organ-wise Exemplar Synthesis

CAMM: Confidence-Aligned Multiview Multimodal Fusion for Brain Disorders Prediction With Imaging Transcriptomics.

MedScaleRE-PF: a prompt-based framework with retrieval-augmented generation, chain-of-thought, and self-verification for scale-specific relation extraction in Chinese medical literature

Prompt Framework for Extracting Scale-Related Knowledge Entities from Chinese Medical Literature: Development and Evaluation Study

DC-GCE Loss: Robust Medical Image Classification Under Label Noise

A Module-Level Polygenic Risk Score-Based NetWAS Framework for Identifying AD Genetic Modules Mediated by Amygdala: An ADNI Study

Trustworthy Enhanced Multi-view Multi-modal Alzheimer’s Disease Prediction with Brain-wide Imaging Transcriptomics Data

Comprehensive review of Transformer‐based models in neuroscience, neurology, and psychiatry

DDASR: Domain-Distance Adapted Super-Resolution Reconstruction of MR Brain Images

TEMINET: A Co-Informative and Trustworthy Multi-Omics Integration Network for Diagnostic Prediction

Multimodal radiomics-based methods using deep learning for prediction of brain metastasis in non-small cell lung cancer with 18F-FDG PET/CT images

Fusion of shallow and deep features from 18F-FDG PET/CT for predicting EGFR-sensitizing mutations in non-small cell lung cancer

“人工智能+脑科学”交叉学科教学模式探索

MOCAT: multi-omics integration with auxiliary classifiers enhanced autoencoder

GREMI: an Explainable Multi-omics Integration Framework for Enhanced Disease Prediction and Module Identification

MR Image Harmonization with Transformer

Adversarially Trained Persistent Homology Based Graph Convolutional Network for Disease Identification Using Brain Connectivity

“人工智能+脑科学”交叉学科人才培养框架探索

预印本

Integration of tissue-specific multi-omics data implicates brain targets for complex neuropsychiatric traits

Image Registration and Predictive Modeling: Learning the Metric on the Space of Diffeomorphisms

Deep Learning for Quality Control of Subcortical Brain 3D Shape Models

Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging

研究方向