An interpretable model for predicting side effects of analgesics for osteoarthritis. - Liangliang Liu 001; Jianxin Wang 001; Min Li 007; Fang-Xiang Wu; Hong-Dong Li; Ying Yu; Zhihui Fei (BIBM, 2017)

Multi-scale Deep Convolutional Neural Network for Stroke Lesions Segmentation on CT Images. - Liangliang Liu 001; Shuai Yang; Li Meng; Min Li 007; Jianxin Wang 001 (BrainLes@MICCAI (1), 2018)

Multi-level Glioma Segmentation using 3D U-Net Combined Attention Mechanism with Atrous Convolution. - Jianhong Cheng; Jin Liu 012; Liangliang Liu 001; Yi Pan 001; Jianxin Wang 001 (BIBM, 2019)

Tentative diagnosis prediction via deep understanding of patient narratives. - Ying Yu; Min Li 007; Liangliang Liu 001; Fang-Xiang Wu; Jianxin Wang 001 (BIBM, 2019)

Clinical big data and deep learning: Applications, challenges, and future outlooks. - Ying Yu; Min Li 007; Liangliang Liu 001; Yaohang Li; Jianxin Wang 001 (Big Data Min. Anal., 2019)

Efficient multi-kernel DCNN with pixel dropout for stroke MRI segmentation. - Liangliang Liu 001; Fang-Xiang Wu; Jianxin Wang 001 (Neurocomputing, 2019)

Automatic ICD code assignment of Chinese clinical notes based on multilayer attention BiRNN. - Ying Yu; Min Li 007; Liangliang Liu 001; Zhihui Fei; Fang-Xiang Wu; Jianxin Wang 001 (J. Biomed. Informatics, 2019)

Local Adaptive U-net for Medical Image Segmentation. - Ning Liu; Liangliang Liu 001; Jianxin Wang 001 (BIBM, 2020)

A survey on U-shaped networks in medical image segmentations. - Liangliang Liu 001; Jianhong Cheng; Quan Quan; Fang-Xiang Wu; Yu-Ping Wang 002; Jianxin Wang 001 (Neurocomputing, 2020)

Deep convolutional neural network for accurate segmentation and quantification of white matter hyperintensities. - Liangliang Liu 001; Shaowu Chen; Xiaofeng Zhu 001; Xing-Ming Zhao; Fang-Xiang Wu; Jianxin Wang 001 (Neurocomputing, 2020)

Attention convolutional neural network for accurate segmentation and quantification of lesions in ischemic stroke disease. - Liangliang Liu 001; Lukasz A. Kurgan; Fang-Xiang Wu; Jianxin Wang 001 (Medical Image Anal., 2020)

Deep convolutional neural network for automatically segmenting acute ischemic stroke lesion in multi-modality MRI. - Liangliang Liu 001; Shaowu Chen; Fuhao Zhang; Fang-Xiang Wu; Yi Pan 001; Jianxin Wang 001 (Neural Comput. Appl., 2020)

Multi-Receptive-Field CNN for Semantic Segmentation of Medical Images. - Liangliang Liu 001; Fang-Xiang Wu; Yu-Ping Wang 002; Jianxin Wang 001 (IEEE J. Biomed. Health Informatics, 2020)

Alzheimer's Disease Classification Using 2D Convolutional Neural Networks. - Gongbo Liang; Xin Xing 002; Liangliang Liu 001; Yu Zhang 094; Qi Ying; Ai-Ling Lin; Nathan Jacobs (EMBC, 2021)

Multi-Modal Data Analysis for Alzheimer's Disease Diagnosis: An Ensemble Model Using Imagery and Genetic Features. - Qi Ying; Xin Xing 002; Liangliang Liu 001; Ai-Ling Lin; Nathan Jacobs; Gongbo Liang (EMBC, 2021)

Co-optimization Learning Network for MRI Segmentation of Ischemic Penumbra Tissues. - Liangliang Liu 001; Jing Zhang; Jin-xiang Wang; Shufeng Xiong; Hui Zhang (Frontiers Neuroinformatics, 2021)

Beware the Black-Box of Medical Image Generation: an Uncertainty Analysis by the Learned Feature Space. - Yunni Qu; David Yan; Eric Xing; Fengbo Zheng; Jie Zhang 092; Liangliang Liu 001; Gongbo Liang (EMBC, 2022)

Neural Network Decision-Making Criteria Consistency Analysis via Inputs Sensitivity. - Eric Xing; Liangliang Liu 001; Xin Xing 002; Yunni Qu; Nathan Jacobs; Gongbo Liang (ICPR, 2022)

Development of CNN models for the enteral feeding tube positioning assessment on a small scale data set. - Gongbo Liang; Halemane Ganesh; Dylan Steffe; Liangliang Liu 001; Nathan Jacobs; Jie Zhang 092 (BMC Medical Imaging, 2022)

LLRHNet: Multiple Lesions Segmentation Using Local-Long Range Features. - Liangliang Liu 001; Ying Wang; Jing Chang; Pei Zhang; Gongbo Liang; Hui Zhang (Frontiers Neuroinformatics, 2022)

An enhanced multi-modal brain graph network for classifying neuropsychiatric disorders. - Liangliang Liu 001; Yu-Ping Wang 002; Yi Wang; Pei Zhang; Shufeng Xiong (Medical Image Anal., 2022)

Automated Diagnosis of COVID-19 Using Deep Supervised Autoencoder With Multi-View Features From CT Images. - Jianhong Cheng; Wei Zhao 040; Jin Liu 012; Xingzhi Xie; Shangjie Wu; Liangliang Liu 001; Hailin Yue; Junjian Li; Jianxin Wang 001; Jun Liu 075 (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

An Ensemble Hybrid Feature Selection Method for Neuropsychiatric Disorder Classification. - Liangliang Liu 001; Shaojie Tang 002; Fang-Xiang Wu; Yu-Ping Wang 002; Jianxin Wang 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

A spatiotemporal correlation deep learning network for brain penumbra disease. - Liangliang Liu 001; Pei Zhang; Gongbo Liang; Shufeng Xiong; Jianxin Wang 001; Guang Zheng (Neurocomputing, 2023)

TRIMOON: Two-Round Inconsistency-based Multi-modal fusion Network for fake news detection. - Shufeng Xiong; Guipei Zhang; Vishwash Batra; Lei Xi; Lei Shi; Liangliang Liu 001 (Inf. Fusion, 2023)

Simulated Quantum Mechanics-Based Joint Learning Network for Stroke Lesion Segmentation and TICI Grading. - Liangliang Liu 001; Jing Chang; Gongbo Liang; Shufeng Xiong (IEEE J. Biomed. Health Informatics, 2023)

SASG-GCN: Self-Attention Similarity Guided Graph Convolutional Network for Multi-Type Lower-Grade Glioma Classification. - Liangliang Liu 001; Jing Chang; Pei Zhang; Hongbo Qiao; Shufeng Xiong (IEEE J. Biomed. Health Informatics, 2023)

Hybrid Contextual Semantic Network for Accurate Segmentation and Detection of Small-Size Stroke Lesions From MRI. - Liangliang Liu 001; Jing Chang; Zhihong Liu; Pei Zhang; Xue Xu; Hongcai Shang (IEEE J. Biomed. Health Informatics, 2023)

Patch-Based Coupled Attention Network to Predict MSI Status in Colon Cancer. - Xiangyu Li; Liangliang Liu 001 (ISBRA (2), 2024)

A Hybrid Feature Fusion Network for Predicting HER2 Status on H &E-Stained Histopathology Images. - Pei Zhang; Zhihong Liu; Liangliang Liu 001 (ISBRA (2), 2024)

A multi-modal extraction integrated model for neuropsychiatric disorders classification. - Liangliang Liu 001; Zhihong Liu; Jing Chang; Xue Xu (Pattern Recognit., 2024)

Collaborative Transfer Network for Multi-Classification of Breast Cancer Histopathological Images. - Liangliang Liu 001; Ying Wang; Pei Zhang; Hongbo Qiao; Tong Sun; Hui Zhang; Xue Xu; Hongcai Shang (IEEE J. Biomed. Health Informatics, 2024)

GVC-YOLO: A Lightweight Real-Time Detection Method for Cotton Aphid-Damaged Leaves Based on Edge Computing. - Zhenyu Zhang; Yunfan Yang; Xin Xu; Liangliang Liu 001; Jibo Yue; Ruifeng Ding; Yanhui Lu; Jie Liu; Hongbo Qiao (Remote. Sens., 2024)

H-Net: Heterogeneous Neural Network for Multi-Classification of Neuropsychiatric Disorders. - Liangliang Liu 001; Jinpu Xie; Jing Chang; Zhihong Liu; Tong Sun; Hongbo Qiao; Gongbo Liang; Wei Guo 029 (IEEE J. Biomed. Health Informatics, 2024)

Automatic porcine diarrhea viruses classification using pathological images and hybrid semantic neural network. - Liangliang Liu 001; Jinpu Xie; Fengjie Zhao; Jing Chang; Yurong Yang; Zi-tong Guo; Longxian Zhang (Comput. Biol. Medicine, 2025)

Transformers in pathological image analysis: A survey. - Liangliang Liu 001; Zhihong Liu; Jinpu Xie; Hongbo Qiao; Jing Chang (Eng. Appl. Artif. Intell., 2025)