| A survey of MRI-based brain tumor segmentation methods Jin Liu, Min Li, Jianxin Wang, Fang-Xiang Wu, Tianming Liu, Yi Pan Tsinghua Science and Technology 19 (6), 578-595, 2014 | 523 | 2014 |
| Applications of deep learning to MRI images: A survey J Liu, Y Pan, M Li, Z Chen, L Tang, C Lu, J Wang Big Data Mining and Analytics 1 (1), 1-18, 2018 | 326 | 2018 |
| Classification of autism spectrum disorder by combining brain connectivity and deep neural network classifier Yazhou Kong, Jianliang Gao, Yunpei Xu, Yi Pan, Jianxin Wang, Jin Liu Neurocomputing 324, 63-68, 2019 | 243 | 2019 |
| Classification of alzheimer's disease using whole brain hierarchical network J Liu, M Li, W Lan, FX Wu, Y Pan, J Wang IEEE/ACM transactions on computational biology and bioinformatics 15 (2 …, 2018 | 215 | 2018 |
| LDAP: a web server for lncRNA-disease association prediction W Lan, M Li, K Zhao, J Liu, FX Wu, Y Pan, J Wang Bioinformatics 33 (3), 458-460, 2016 | 214 | 2016 |
| Complex brain network analysis and its applications to brain disorders: a survey J Liu, M Li, Y Pan, W Lan, R Zheng, FX Wu, J Wang Complexity 2017 (1), 8362741, 2017 | 181 | 2017 |
| Predicting microRNA-disease associations based on improved microRNA and disease similarities W Lan, J Wang, M Li, J Liu, FX Wu, Y Pan IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) 15 …, 2018 | 142 | 2018 |
| A Fully Automated Multimodal MRI-based Multi-task Learning for Glioma Segmentation and IDH Genotyping J Cheng, J Liu, H Kuang, J Wang IEEE Transactions on Medical Imaging 41 (6), 1520-1532, 2022 | 119 | 2022 |
| Predicting drug–target interaction using positive-unlabeled learning Wei Lan, Jianxin Wang, Min Li, Jin Liu, Yaohang Li, Fang-Xiang Wu, Yi Pan Neurocomputing 206, 50-57, 2016 | 110 | 2016 |
| AIMAFE: Autism spectrum disorder identification with multi-atlas deep feature representation and ensemble learning Y Wang, J Wang, FX Wu, R Hayrat, J Liu Journal of Neuroscience Methods 343 (108840), 2020 | 86 | 2020 |
| Improving Alzheimer‘s disease classification by combining multiple measures J Liu, J Wang, Z Tang, B Hu, F Wu, Y Pan IEEE/ACM transactions on computational biology and bioinformatics 15 (5 …, 2018 | 77 | 2018 |
| Improved ASD Classification using Dynamic Functional Connectivity and Multi-task Feature Selection J Liu, Y Sheng, W Lan, R Guo, Y Wang, J Wang Pattern Recognition Letters 138, 82-87, 2020 | 74 | 2020 |
| LDICDL: LncRNA-disease association identification based on collaborative deep learning W Lan, D Lai, Q Chen, X Wu, B Chen, J Liu, J Wang, YPP Chen IEEE/ACM Transactions on Computational Biology and Bioinformatics 19 (3 …, 2022 | 72 | 2022 |
| Alzheimer's Disease Classification Based on Individual Hierarchical Networks Constructed with 3D Texture Features Jin Liu, Jianxin Wang, Bin Hu, Fang-Xiang Wu, Yi Pan IEEE transactions on nanobioscience 16 (6), 428-437, 2017 | 70 | 2017 |
| ILDMSF: inferring associations between long non-coding RNA and disease based on multi-similarity fusion Q Chen, D Lai, W Lan, X Wu, B Chen, J Liu, YPP Chen, J Wang IEEE/ACM Transactions on Computational Biology and Bioinformatics 18 (3 …, 2021 | 66 | 2021 |
| KGANCDA: predicting circRNA-disease associations based on knowledge graph attention network W Lan, Y Dong, Q Chen, R Zheng, J Liu, Y Pan, YPP Chen Briefings in Bioinformatics 23 (1), bbab494, 2022 | 65 | 2022 |
| Phase prediction of Ni-base superalloys via high-throughput experiments and machine learning Z Qin, Z Wang, Y Wang, L Zhang, W Li, J Liu, Z Wang, Z Li, J Pan, L Zhao, ... Materials Research Letters 9 (1), 32-40, 2021 | 64 | 2021 |
| Enhancing the feature representation of multi-modal MRI data by combining multi-view information for MCI classification J Liu, Y Pan, FX Wu, J Wang Neurocomputing 400, 322-332, 2020 | 61 | 2020 |
| MAGE: Automatic diagnosis of autism spectrum disorders using multi-atlas graph convolutional networks and ensemble learning Y Wang, J Liu, Y Xiang, J Wang, Q Chen, J Chong Neurocomputing 469, 346-353, 2022 | 59 | 2022 |
| Multimodal disentangled variational autoencoder with game theoretic interpretability for glioma grading J Cheng, M Gao, J Liu, H Yue, H Kuang, J Liu, J Wang IEEE Journal of Biomedical and Health Informatics 26 (2), 673 - 684, 2022 | 49 | 2022 |
Jianxin WangSchool of Computer Science and Engineering, Central South universityVerified email at mail.csu.edu.cn
