Development and validation of an interpretable deep learning framework for Alzheimer’s disease classification S Qiu, PS Joshi, MI Miller, C Xue, X Zhou, C Karjadi, GH Chang, AS Joshi, ... Brain 143 (6), 1920-1933, 2020 | 395 | 2020 |
Enhancing magnetic resonance imaging-driven Alzheimer’s disease classification performance using generative adversarial learning X Zhou, S Qiu, PS Joshi, C Xue, RJ Killiany, AZ Mian, SP Chin, R Au, ... Alzheimer's research & therapy 13 (1), 1-11, 2021 | 75 | 2021 |
Single-cell genomics and regulatory networks for 388 human brains PS Emani, JJ Liu, D Clarke, M Jensen, J Warrell, C Gupta, R Meng, ... Science 384 (6698), eadi5199, 2024 | 34 | 2024 |
Application of seq2seq models on code correction S Huang, X Zhou, S Chin Frontiers in artificial intelligence 4, 590215, 2021 | 19 | 2021 |
Mixed spatio-temporal neural networks on real-time prediction of crimes X Zhou, X Wang, G Brown, C Wang, P Chin 2021 20th IEEE International Conference on Machine Learning and Applications …, 2021 | 6 | 2021 |
Deep learning for risk-based stratification of cognitively impaired individuals MF Romano, X Zhou, AR Balachandra, MF Jadick, S Qiu, DA Nijhawan, ... iScience 26 (9), 2023 | 5 | 2023 |
Enhancing MR imaging driven Alzheimer’s disease classification performance using generative adversarial learning X Zhou, S Qiu, PS Joshi, C Xue, RJ Killiany, A Mian, SP Chin, R Au, ... medRxiv, 2020.07. 22.20159814, 2020 | 4 | 2020 |
Domain specific inpainting with concurrently pretrained generative adversarial networks X Zhou, C Wang, Y Xu, X Wang, P Chin 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2017 | 4 | 2017 |
Deep learning-driven risk-based subtyping of cognitively impaired individuals MF Romano, X Zhou, AR Balachandra, MF Jadick, S Qiu, DA Nijhawan, ... medRxiv, 2021.12. 08.21267495, 2021 | 2 | 2021 |
Learning in Parrondo’s Paradox X Zhou, X Wang, P Chin THE 29TH INTERNATIONAL CONFERENCE ON GAME THEORY, 2018 | 2 | 2018 |
Adversarial learning for MRI reconstruction and classification of cognitively impaired individuals X Zhou, AR Balachandra, MF Romano, SP Chin, R Au, VB Kolachalama IEEE Access, 2024 | 1 | 2024 |
Deep learning analysis of fMRI data for predicting Alzheimer’s Disease: A focus on convolutional neural networks and model interpretability X Zhou, S Kedia, R Meng, M Gerstein Plos one 19 (12), e0312848, 2024 | | 2024 |
Adversarial Learning for MRI Reconstruction and Classification of Cognitively Impaired Individuals (P1-9.008) A Balachandra, X Zhou, M Romano, V Kolachalama Neurology 102 (17_supplement_1), 2895, 2024 | | 2024 |
Network-based drug repurposing for psychiatric disorders using single-cell genomics C Gupta, N Cohen Kalafut, D Clarke, J Choi, KH Arachchilage, S Khullar, ... medRxiv, 2024.12. 01.24318008, 2024 | | 2024 |
Non-competitive and competitive deep learning for imaging applications X Zhou Boston University, 2022 | | 2022 |
Comparative analysis of cerebrospinal fluid markers and multimodal imaging in predicting Alzheimer’s disease progression MF Romano, A Balachandra, X Zhou, M Jadick, S Qiu, D Nijhawan, ... Alzheimer's & Dementia 17, e054457, 2021 | | 2021 |
Application of seq2seq models on code correction S Chin, S Huang, X Zhou | | 2020 |
A Deep Learning Framework for Risk-Based Stratification of Cognitively Impaired Individuals MF Romano, X Zhou, AR Balachandra, M Jadick, S Qiu, D Nijhawan, ... | | |