| A multi-task, multi-stage deep transfer learning model for early prediction of neurodevelopment in very preterm infants L He, H Li, J Wang, M Chen, E Gozdas, JR Dillman, NA Parikh Scientific Reports 10 (1), 15072, 2020 | 49 | 2020 |
| A multichannel deep neural network model analyzing multiscale functional brain connectome data for attention deficit hyperactivity disorder detection M Chen, H Li, J Wang, JR Dillman, NA Parikh, L He Radiology: Artificial Intelligence 2 (1), e190012, 2019 | 45 | 2019 |
| Early prediction of cognitive deficit in very preterm infants using brain structural connectome with transfer learning enhanced deep convolutional neural networks M Chen, H Li, J Wang, W Yuan, M Altaye, NA Parikh, L He Frontiers in neuroscience 14, 858, 2020 | 32 | 2020 |
| Deep multimodal learning from MRI and clinical data for early prediction of neurodevelopmental deficits in very preterm infants L He, H Li, M Chen, J Wang, M Altaye, JR Dillman, NA Parikh Frontiers in neuroscience 15, 753033, 2021 | 24 | 2021 |
| ConCeptCNN: A novel multi‐filter convolutional neural network for the prediction of neurodevelopmental disorders using brain connectome M Chen, H Li, H Fan, JR Dillman, H Wang, M Altaye, B Zhang, NA Parikh, ... Medical Physics, 2022 | 21 | 2022 |
| Diffusion MRI Microstructural Abnormalities at Term-Equivalent Age Are Associated with Neurodevelopmental Outcomes at 3 Years of Age in Very Preterm Infants M.N. Parikh, M. Chen, A. Braimah, J. Kline, K. McNally, J.W. Logan, L. Tamm ... American Journal of Neuroradiology, 2021 | 13 | 2021 |
| Objective and automated detection of diffuse white matter abnormality in preterm infants using deep convolutional neural networks H Li, NA Parikh, J Wang, S Merhar, M Chen, M Parikh, S Holland, L He Frontiers in neuroscience 13, 610, 2019 | 13 | 2019 |
| Automatic segmentation of diffuse white matter abnormality on T2-weighted brain MR images using deep learning in very preterm infants H Li, M Chen, J Wang, VSP Illapani, NA Parikh, L He Radiology: Artificial Intelligence 3 (3), e200166, 2021 | 11 | 2021 |
| Early prediction of cognitive deficits in very preterm infants using graph convolutional networks with brain structural connectome Hailong Li, Ming Chen, Jinghua Wang, Nehal A. Parikh, Lili He International Society for Magnetic Resonance in Medicine, 2021 | 1 | 2021 |
| A semi-supervised graph convolutional network for early prediction of motor impairments in very preterm infants using brain connectome Hailong Li, Ming Chen, Jinghua Wang, Nehal A. Parikh, Lili He International Society for Magnetic Resonance in Medicine, 2021 | | 2021 |
| Integration of multi-modality MRI for early prediction of cognitive deficits using deep learning Lili He, Hailong Li, Ming Chen, Jinghua Wang, Mekibib Altaye, Nehal Parikh Organization for Human Brain Mapping, 2021 | | 2021 |
| Automated Segmentation of Diffuse White Matter Abnormality in Very Preterm Infants using U-Net Hailong Li, Ming Chen, Jinghua Wang, Nehal A. Parikh, and Lili He Organization for Human Brain Mapping, 2021 | | 2021 |
| A novel multi-filter convolutional neural network for prediction of cognitive deficits using brain structural connectome in very preterm infants Ming Chen, Hailong Li, Jinghua Wang, Nehal A. Parikh, Lili He International Society for Magnetic Resonance in Medicine, 2021 | | 2021 |
| Image Synthesis in Multi-Contrast MRI using Wasserstein Cycle-Consistent Adversarial Network”, Organization for Human Brain Mapping Ming Chen, Hailong Li, Jinghua Wang, Jonathan R. Dillman, Andrew T. Trout ... Organization for Human Brain Mapping, 2021 | | 2021 |
| A multi-channel deep neural network model analyzing multiscale functional brain connectome data for ADHD detection Ming Chen, Hailong Li, Jinghua Wang, Jonathan R. Dillman, Nehal A. Parikh ... ISMRM, 2020 | | 2020 |
| A deep transfer learning model for early prediction of cognitive deficits using brain structural connectome in very preterm infants Ming Chen, Hailong Li, Jinghua Wang, Weihong Yuan, Adebayo Braimah, Mekibib ... International Society for Magnetic Resonance in Medicine, 2020 | | 2020 |
| A multi-task deep transfer learning model for prediction of neurodevelopmental deficits in very preterm infants Lili He, Hailong Li, Jinghua Wang, Ming Chen, Jonathan R. Dillman, Nehal A ... International Society for Magnetic Resonance in Medicine, 2020 | | 2020 |
| Segmentation of Diffuse White Matter Abnormality in Preterm Infants using Deep Convolutional Neural Networks Hailong Li, Nehal A. Parikh, Jinghua Wang ,Stephanie Merhar, Ming Chen ... International Society for Magnetic Resonance in Medicine, 2019 | | 2019 |
| A machine learning model using T2-weighted FLAIR radiomics features to predict patient outcome in ICH Jinghua Wang, Ming Chen, Lili He, Hailong Li, Vivek Khandwala, David Wang ... International Society for Magnetic Resonance in Medicine, 2019 | | 2019 |
| A Deep Transfer Learning Model to Predict Patient Outcome in ICH using the Fusion of Clinical and Fluid-Attenuated Inversion Recovery Imaging Data Jinghua Wang, Ming Chen, Lili He, Hailong Li, Vivek Khandwala, David Wang ... International Society for Magnetic Resonance in Medicine, 2019 | | 2019 |
