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ORCIDNicha C. Dvornek
Nicha Chitphakdithai
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- affiliation: Yale University, New Haven, CT, USA
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Journal Articles
- 2024
[j10]Xueqi Guo
, Luyao Shi, Xiongchao Chen, Qiong Liu, Bo Zhou, Huidong Xie, Yi-Hwa Liu, Richard Palyo, Edward J. Miller, Albert J. Sinusas, Lawrence H. Staib, Bruce Spottiswoode, Chi Liu, Nicha C. Dvornek:
TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction. Medical Image Anal. 96: 103190 (2024)- [j9]Yinchi Zhou, Tianqi Chen, Jun Hou, Huidong Xie, Nicha C. Dvornek, S. Kevin Zhou, David L. Wilson, James S. Duncan, Chi Liu, Bo Zhou:
Cascaded Multi-path Shortcut Diffusion Model for Medical Image Translation. Medical Image Anal. 98: 103300 (2024) - 2023
- [j8]Liang Peng, Nan Wang, Nicha C. Dvornek, Xiaofeng Zhu, Xiaoxiao Li:
FedNI: Federated Graph Learning With Network Inpainting for Population-Based Disease Prediction. IEEE Trans. Medical Imaging 42(7): 2032-2043 (2023) - [j7]Xueqi Guo, Bo Zhou, Xiongchao Chen, Ming-Kai Chen, Chi Liu, Nicha C. Dvornek:
MCP-Net: Introducing Patlak Loss Optimization to Whole-Body Dynamic PET Inter-Frame Motion Correction. IEEE Trans. Medical Imaging 42(12): 3512-3523 (2023) - 2022
- [j6]Xueqi Guo, Bo Zhou, David Pigg, Bruce Spottiswoode, Michael E. Casey, Chi Liu, Nicha C. Dvornek:
Unsupervised inter-frame motion correction for whole-body dynamic PET using convolutional long short-term memory in a convolutional neural network. Medical Image Anal. 80: 102524 (2022) - 2021
- [j5]Markus D. Schirmer, Archana Venkataraman, Islem Rekik, Minjeong Kim, Stewart H. Mostofsky, Mary Beth Nebel, Keri Rosch, Karen Seymour, Deana Crocetti, Hassna Irzan, Michael Hütel, Sébastien Ourselin, Neil Marlow, Andrew Melbourne, Egor Levchenko, Shuo Zhou, Mwiza Kunda, Haiping Lu, Nicha C. Dvornek, Juntang Zhuang, Gideon Pinto, Sandip Samal, Jennings Zhang, Jorge L. Bernal-Rusiel, Rudolph Pienaar, Ai Wern Chung:
Neuropsychiatric disease classification using functional connectomics - results of the connectomics in neuroimaging transfer learning challenge. Medical Image Anal. 70: 101972 (2021) - [j4]Xiaoxiao Li, Yuan Zhou, Nicha C. Dvornek, Muhan Zhang, Siyuan Gao, Juntang Zhuang, Dustin Scheinost, Lawrence H. Staib, Pamela Ventola, James S. Duncan:
BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis. Medical Image Anal. 74: 102233 (2021) - [j3]Luyao Shi, Yihuan Lu, Nicha C. Dvornek, Christopher A. Weyman, Edward J. Miller, Albert J. Sinusas, Chi Liu:
Automatic Inter-Frame Patient Motion Correction for Dynamic Cardiac PET Using Deep Learning. IEEE Trans. Medical Imaging 40(12): 3293-3304 (2021) - 2020
- [j2]Xiaoxiao Li, Yufeng Gu, Nicha C. Dvornek, Lawrence H. Staib, Pamela Ventola, James S. Duncan:
Multi-site fMRI analysis using privacy-preserving federated learning and domain adaptation: ABIDE results. Medical Image Anal. 65: 101765 (2020) - [j1]Fan Zhang, Nicha C. Dvornek, Junlin Yang, Julius Chapiro, Jim Duncan:
Layer Embedding Analysis in Convolutional Neural Networks for Improved Probability Calibration and Classification. IEEE Trans. Medical Imaging 39(11): 3331-3342 (2020)
Conference and Workshop Papers
- 2024
- [c42]Yuexi Du, Regina J. Hooley, John Lewin, Nicha C. Dvornek:
SIFT-DBT: Self-Supervised Initialization and Fine-Tuning for Imbalanced Digital Breast Tomosynthesis Image Classification. ISBI 2024: 1-5 - [c41]Peiyu Duan, Nicha C. Dvornek, Jiyao Wang, Jeffrey Eilbott, Yuexi Du, Denis G. Sukhodolsky, James S. Duncan:
Spectral Brain Graph Neural Network for Prediction of Anxiety in Children with Autism Spectrum Disorder. ISBI 2024: 1-5 - [c40]Yuexi Du, Brian Chang, Nicha C. Dvornek:
CLEFT: Language-Image Contrastive Learning with Efficient Large Language Model and Prompt Fine-Tuning. MICCAI (12) 2024: 465-475 - 2023
- [c39]Xueqi Guo, Luyao Shi, Xiongchao Chen, Bo Zhou, Qiong Liu, Huidong Xie, Yi-Hwa Liu, Richard Palyo, Edward J. Miller, Albert J. Sinusas, Bruce Spottiswoode, Chi Liu, Nicha C. Dvornek:
TAI-GAN: Temporally and Anatomically Informed GAN for Early-to-Late Frame Conversion in Dynamic Cardiac PET Motion Correction. SASHIMI@MICCAI 2023: 64-74 - [c38]Jiyao Wang, Nicha C. Dvornek, Lawrence H. Staib, James S. Duncan:
Learning Sequential Information in Task-Based fMRI for Synthetic Data Augmentation. MLCN@MICCAI 2023: 79-88 - [c37]Nicha C. Dvornek, Catherine Sullivan, James S. Duncan, Abha R. Gupta:
Copy Number Variation Informs fMRI-Based Prediction of Autism Spectrum Disorder. MLCN@MICCAI 2023: 133-142 - 2022
- [c36]Juntang Zhuang, Boqing Gong, Liangzhe Yuan, Yin Cui, Hartwig Adam, Nicha C. Dvornek, Sekhar Tatikonda, James S. Duncan, Ting Liu:
Surrogate Gap Minimization Improves Sharpness-Aware Training. ICLR 2022 - [c35]Xueqi Guo, Bo Zhou, Xiongchao Chen, Chi Liu, Nicha C. Dvornek:
MCP-Net: Inter-frame Motion Correction with Patlak Regularization for Whole-body Dynamic PET. MICCAI (4) 2022: 163-172 - 2021
- [c34]Juntang Zhuang, Nicha C. Dvornek, Sekhar Tatikonda, James S. Duncan:
MALI: A memory efficient and reverse accurate integrator for Neural ODEs. ICLR 2021 - [c33]Juntang Zhuang, Nicha C. Dvornek, Sekhar Tatikonda, Xenophon Papademetris, Pamela Ventola, James S. Duncan:
Multiple-Shooting Adjoint Method for Whole-Brain Dynamic Causal Modeling. IPMI 2021: 58-70 - [c32]Shiyu Wang, Nicha C. Dvornek:
A Metamodel Structure For Regression Analysis: Application To Prediction Of Autism Spectrum Disorder Severity. ISBI 2021: 1338-1341 - [c31]Juntang Zhuang, Yifan Ding, Tommy Tang, Nicha C. Dvornek, Sekhar Tatikonda, James S. Duncan:
Momentum Centering and Asynchronous Update for Adaptive Gradient Methods. NeurIPS 2021: 28249-28260 - 2020
- [c30]Juntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li, Sekhar Tatikonda, Xenophon Papademetris, James S. Duncan:
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE. ICML 2020: 11639-11649 - [c29]Nicha C. Dvornek, Pamela Ventola, James S. Duncan:
Estimating Reproducible Functional Networks Associated with Task Dynamics Using Unsupervised LSTMS. ISBI 2020: 1-4 - [c28]Xiaoxiao Li, Nicha C. Dvornek, Juntang Zhuang, Pamela Ventola, James S. Duncan:
Graph embedding using Infomax for ASD classification and brain functional difference detection. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2020: 1131702 - [c27]Junlin Yang, Xiaoxiao Li, Daniel H. Pak, Nicha C. Dvornek, Julius Chapiro, Ming De Lin, James S. Duncan:
Cross-Modality Segmentation by Self-supervised Semantic Alignment in Disentangled Content Space. DART/DCL@MICCAI 2020: 52-61 - [c26]Nicha C. Dvornek, Xiaoxiao Li, Juntang Zhuang, Pamela Ventola, James S. Duncan:
Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity. MLMI@MICCAI 2020: 363-372 - [c25]Xiaoxiao Li, Yuan Zhou, Nicha C. Dvornek, Muhan Zhang, Juntang Zhuang, Pamela Ventola, James S. Duncan:
Pooling Regularized Graph Neural Network for fMRI Biomarker Analysis. MICCAI (7) 2020: 625-635 - [c24]Xiaoxiao Li, Yuan Zhou, Nicha C. Dvornek, Yufeng Gu, Pamela Ventola, James S. Duncan:
Efficient Shapley Explanation for Features Importance Estimation Under Uncertainty. MICCAI (1) 2020: 792-801 - [c23]Juntang Zhuang, Tommy Tang, Yifan Ding, Sekhar Tatikonda, Nicha C. Dvornek, Xenophon Papademetris, James S. Duncan:
AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients. NeurIPS 2020 - 2019
- [c22]Junlin Yang, Nicha C. Dvornek, Fan Zhang, Juntang Zhuang, Julius Chapiro, Ming De Lin, James S. Duncan:
Domain-Agnostic Learning With Anatomy-Consistent Embedding for Cross-Modality Liver Segmentation. ICCV Workshops 2019: 323-331 - [c21]Juntang Zhuang, Junlin Yang, Lin Gu, Nicha C. Dvornek:
ShelfNet for Fast Semantic Segmentation. ICCV Workshops 2019: 847-856 - [c20]Juntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li, Junlin Yang, James S. Duncan:
Decision explanation and feature importance for invertible networks. ICCV Workshops 2019: 4235-4239 - [c19]Xiaoxiao Li, Nicha C. Dvornek, Yuan Zhou, Juntang Zhuang, Pamela Ventola, James S. Duncan:
Efficient Interpretation of Deep Learning Models Using Graph Structure and Cooperative Game Theory: Application to ASD Biomarker Discovery. IPMI 2019: 718-730 - [c18]Juntang Zhuang, Nicha C. Dvornek, Qingyu Zhao, Xiaoxiao Li, Pamela Ventola, James S. Duncan:
Prediction of Treatment Outcome for Autism from Structure of the Brain Based On Sure Independence Screening. ISBI 2019: 404-408 - [c17]Junlin Yang, Nicha C. Dvornek, Fan Zhang, Julius Chapiro, Ming De Lin, James S. Duncan:
Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation. MICCAI (2) 2019: 255-263 - [c16]Nicha C. Dvornek, Xiaoxiao Li, Juntang Zhuang, James S. Duncan:
Jointly Discriminative and Generative Recurrent Neural Networks for Learning from fMRI. MLMI@MICCAI 2019: 382-390 - [c15]Xiaoxiao Li, Nicha C. Dvornek, Yuan Zhou, Juntang Zhuang, Pamela Ventola, James S. Duncan:
Graph Neural Network for Interpreting Task-fMRI Biomarkers. MICCAI (5) 2019: 485-493 - [c14]Juntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li, Pamela Ventola, James S. Duncan:
Invertible Network for Classification and Biomarker Selection for ASD. MICCAI (3) 2019: 700-708 - 2018
- [c13]Juntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li, Daniel Y.-J. Yang, Pamela Ventola, James S. Duncan:
Prediction of Pivotal response treatment outcome with task fMRI using random forest and variable selection. ISBI 2018: 97-100 - [c12]Nicha C. Dvornek, Pamela Ventola, James S. Duncan:
Combining phenotypic and resting-state fMRI data for autism classification with recurrent neural networks. ISBI 2018: 725-728 - [c11]Xiaoxiao Li, Nicha C. Dvornek, Xenophon Papademetris, Juntang Zhuang, Lawrence H. Staib, Pamela Ventola, James S. Duncan:
2-Channel convolutional 3D deep neural network (2CC3D) for fMRI analysis: ASD classification and feature learning. ISBI 2018: 1252-1255 - [c10]Juntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li, Pamela Ventola, James S. Duncan:
Prediction of Severity and Treatment Outcome for ASD from fMRI. PRIME@MICCAI 2018: 9-17 - [c9]Xiaoxiao Li, Nicha C. Dvornek, Juntang Zhuang, Pamela Ventola, James S. Duncan:
Brain Biomarker Interpretation in ASD Using Deep Learning and fMRI. MICCAI (3) 2018: 206-214 - [c8]Nicha C. Dvornek, Daniel Y.-J. Yang, Pamela Ventola, James S. Duncan:
Learning Generalizable Recurrent Neural Networks from Small Task-fMRI Datasets. MICCAI (3) 2018: 329-337 - 2017
- [c7]Nicha C. Dvornek, Pamela Ventola, Kevin A. Pelphrey, James S. Duncan:
Identifying Autism from Resting-State fMRI Using Long Short-Term Memory Networks. MLMI@MICCAI 2017: 362-370 - 2012
- [c6]Nicha Chitphakdithai, Veronica L. Chiang, James S. Duncan:
Tracking Metastatic Brain Tumors in Longitudinal Scans via Joint Image Registration and Labeling. STIA 2012: 124-136 - 2011
- [c5]Nicha Chitphakdithai, Veronica L. Chiang, James S. Duncan:
Non-rigid registration of longitudinal brain tumor treatment MRI. EMBC 2011: 4893-4896 - [c4]Nicha Chitphakdithai, Kenneth P. Vives, James S. Duncan:
Registration of brain resection MRI with intensity and location priors. ISBI 2011: 1520-1523 - 2010
- [c3]Nicha Chitphakdithai, James S. Duncan:
Pairwise registration of images with missing correspondences due to resection. ISBI 2010: 1025-1028 - [c2]Nicha Chitphakdithai, James S. Duncan:
Non-rigid Registration with Missing Correspondences in Preoperative and Postresection Brain Images. MICCAI (1) 2010: 367-374 - 2007
- [c1]Ameet Kumar Jain, Michael An, Nicha Chitphakdithai, Gouthami Chintalapani, Gabor Fichtinger:
C-arm calibration: is it really necessary? Medical Imaging: Image-Guided Procedures 2007: 65092U
Editorship
- 2023
- [e2]Ahmed Abdulkadir, Deepti R. Bathula, Nicha C. Dvornek, Sindhuja Tirumalai Govindarajan, Mohamad Habes, Vinod Kumar, Esten H. Leonardsen, Thomas Wolfers, Yiming Xiao:
Machine Learning in Clinical Neuroimaging - 6th International Workshop, MLCN 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings. Lecture Notes in Computer Science 14312, Springer 2023, ISBN 978-3-031-44857-7 [contents] - 2022
- [e1]Ahmed Abdulkadir, Deepti R. Bathula, Nicha C. Dvornek, Mohamad Habes, Seyed Mostafa Kia, Vinod Kumar, Thomas Wolfers:
Machine Learning in Clinical Neuroimaging - 5th International Workshop, MLCN 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings. Lecture Notes in Computer Science 13596, Springer 2022, ISBN 978-3-031-17898-6 [contents]
Informal and Other Publications
- 2024
- [i36]Xueqi Guo, Luyao Shi, Xiongchao Chen, Qiong Liu, Bo Zhou, Huidong Xie, Yi-Hwa Liu, Richard Palyo, Edward J. Miller, Albert J. Sinusas, Lawrence H. Staib, Bruce Spottiswoode, Chi Liu, Nicha C. Dvornek:
TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction. CoRR abs/2402.09567 (2024) - [i35]Yuexi Du, Regina J. Hooley, John Lewin, Nicha C. Dvornek:
SIFT-DBT: Self-supervised Initialization and Fine-Tuning for Imbalanced Digital Breast Tomosynthesis Image Classification. CoRR abs/2403.13148 (2024) - [i34]Yinchi Zhou, Tianqi Chen, Jun Hou, Huidong Xie, Nicha C. Dvornek, S. Kevin Zhou, David L. Wilson, James S. Duncan, Chi Liu, Bo Zhou:
Cascaded Multi-path Shortcut Diffusion Model for Medical Image Translation. CoRR abs/2405.12223 (2024) - [i33]Jiyao Wang, Nicha C. Dvornek, Peiyu Duan, Lawrence H. Staib, Pamela Ventola, James S. Duncan:
STNAGNN: Spatiotemporal Node Attention Graph Neural Network for Task-based fMRI Analysis. CoRR abs/2406.12065 (2024) - [i32]Yuexi Du, Brian Chang, Nicha C. Dvornek:
CLEFT: Language-Image Contrastive Learning with Efficient Large Language Model and Prompt Fine-Tuning. CoRR abs/2407.21011 (2024) - [i31]Yinchi Zhou, Peiyu Duan, Yuexi Du, Nicha C. Dvornek:
Self-Supervised Pre-training Tasks for an fMRI Time-series Transformer in Autism Detection. CoRR abs/2409.12304 (2024) - [i30]Yuexi Du, John A. Onofrey, Nicha C. Dvornek:
Multi-View and Multi-Scale Alignment for Contrastive Language-Image Pre-training in Mammography. CoRR abs/2409.18119 (2024) - 2023
- [i29]Nicha C. Dvornek, Catherine Sullivan, James S. Duncan, Abha R. Gupta:
Copy Number Variation Informs fMRI-based Prediction of Autism Spectrum Disorder. CoRR abs/2308.05122 (2023) - [i28]Xueqi Guo, Luyao Shi, Xiongchao Chen, Bo Zhou, Qiong Liu, Huidong Xie, Yi-Hwa Liu, Richard Palyo, Edward J. Miller, Albert J. Sinusas, Bruce Spottiswoode, Chi Liu, Nicha C. Dvornek:
TAI-GAN: Temporally and Anatomically Informed GAN for early-to-late frame conversion in dynamic cardiac PET motion correction. CoRR abs/2308.12443 (2023) - [i27]Jiyao Wang, Nicha C. Dvornek, Lawrence H. Staib, James S. Duncan:
Learning Sequential Information in Task-based fMRI for Synthetic Data Augmentation. CoRR abs/2308.15564 (2023) - 2022
- [i26]Xueqi Guo, Sule Tinaz, Nicha C. Dvornek:
Early Disease Stage Characterization in Parkinson's Disease from Resting-state fMRI Data Using a Long Short-term Memory Network. CoRR abs/2202.12715 (2022) - [i25]Juntang Zhuang, Boqing Gong, Liangzhe Yuan, Yin Cui, Hartwig Adam, Nicha C. Dvornek, Sekhar Tatikonda, James S. Duncan, Ting Liu:
Surrogate Gap Minimization Improves Sharpness-Aware Training. CoRR abs/2203.08065 (2022) - [i24]Xueqi Guo, Bo Zhou, David Pigg, Bruce Spottiswoode, Michael E. Casey, Chi Liu, Nicha C. Dvornek:
Unsupervised inter-frame motion correction for whole-body dynamic PET using convolutional long short-term memory in a convolutional neural network. CoRR abs/2206.06341 (2022) - 2021
- [i23]Juntang Zhuang, Nicha C. Dvornek, Sekhar Tatikonda, James S. Duncan:
MALI: A memory efficient and reverse accurate integrator for Neural ODEs. CoRR abs/2102.04668 (2021) - [i22]Juntang Zhuang, Nicha C. Dvornek, Sekhar Tatikonda, Xenophon Papademetris, Pamela Ventola, James S. Duncan:
Multiple-shooting adjoint method for whole-brain dynamic causal modeling. CoRR abs/2102.11013 (2021) - [i21]Nicha C. Dvornek, Xiaoxiao Li, Juntang Zhuang, Pamela Ventola, James S. Duncan:
Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity. CoRR abs/2104.07654 (2021) - [i20]Nicha C. Dvornek, Pamela Ventola, James S. Duncan:
Estimating Reproducible Functional Networks Associated with Task Dynamics using Unsupervised LSTMs. CoRR abs/2105.02869 (2021) - [i19]Shiyu Wang, Nicha C. Dvornek:
A Metamodel Structure For Regression Analysis: Application To Prediction Of Autism Spectrum Disorder Severity. CoRR abs/2105.02874 (2021) - [i18]Juntang Zhuang, Yifan Ding, Tommy Tang, Nicha C. Dvornek, Sekhar Tatikonda, James S. Duncan:
Momentum Centering and Asynchronous Update for Adaptive Gradient Methods. CoRR abs/2110.05454 (2021) - [i17]Liang Peng, Nan Wang, Nicha C. Dvornek, Xiaofeng Zhu, Xiaoxiao Li:
FedNI: Federated Graph Learning with Network Inpainting for Population-Based Disease Prediction. CoRR abs/2112.10166 (2021) - 2020
- [i16]Xiaoxiao Li, Yufeng Gu, Nicha C. Dvornek, Lawrence H. Staib, Pamela Ventola, James S. Duncan:
Multi-site fMRI Analysis Using Privacy-preserving Federated Learning and Domain Adaptation: ABIDE Results. CoRR abs/2001.05647 (2020) - [i15]Juntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li, Sekhar Tatikonda, Xenophon Papademetris, James S. Duncan:
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE. CoRR abs/2006.02493 (2020) - [i14]Markus D. Schirmer, Archana Venkataraman, Islem Rekik, Minjeong Kim, Stewart Mostofsky, Mary Beth Nebel, Keri Rosch, Karen Seymour, Deana Crocetti, Hassna Irzan, Michael Hütel, Sébastien Ourselin, Neil Marlow, Andrew Melbourne, Egor Levchenko, Shuo Zhou, Mwiza Kunda, Haiping Lu, Nicha C. Dvornek, Juntang Zhuang, Gideon Pinto, Sandip Samal, Jorge L. Bernal-Rusiel, Rudolph Pienaar, Ai Wern Chung:
Neuropsychiatric Disease Classification Using Functional Connectomics - Results of the Connectomics in NeuroImaging Transfer Learning Challenge. CoRR abs/2006.03611 (2020) - [i13]Xiaoxiao Li, Yuan Zhou, Nicha C. Dvornek, Muhan Zhang, Juntang Zhuang, Pamela Ventola, James S. Duncan:
Pooling Regularized Graph Neural Network for fMRI Biomarker Analysis. CoRR abs/2007.14589 (2020) - [i12]Juntang Zhuang, Tommy Tang, Yifan Ding, Sekhar Tatikonda, Nicha C. Dvornek, Xenophon Papademetris, James S. Duncan:
AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients. CoRR abs/2010.07468 (2020) - 2019
- [i11]Xiaoxiao Li, Nicha C. Dvornek, Yuan Zhou, Juntang Zhuang, Pamela Ventola, James S. Duncan:
Graph Neural Network for Interpreting Task-fMRI Biomarkers. CoRR abs/1907.01661 (2019) - [i10]Juntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li, Pamela Ventola, James S. Duncan:
Invertible Network for Classification and Biomarker Selection for ASD. CoRR abs/1907.09729 (2019) - [i9]Junlin Yang, Nicha C. Dvornek, Fan Zhang, Julius Chapiro, Ming De Lin, James S. Duncan:
Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation. CoRR abs/1907.13590 (2019) - [i8]Xiaoxiao Li, Nicha C. Dvornek, Juntang Zhuang, Pamela Ventola, James S. Duncan:
Graph Embedding Using Infomax for ASD Classification and Brain Functional Difference Detection. CoRR abs/1908.04769 (2019) - [i7]Junlin Yang, Nicha C. Dvornek, Fan Zhang, Juntang Zhuang, Julius Chapiro, Ming De Lin, James S. Duncan:
Domain-Agnostic Learning with Anatomy-Consistent Embedding for Cross-Modality Liver Segmentation. CoRR abs/1908.10489 (2019) - [i6]Juntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li, Junlin Yang, James S. Duncan:
Decision Explanation and Feature Importance for Invertible Networks. CoRR abs/1910.00406 (2019) - [i5]Nicha C. Dvornek, Xiaoxiao Li, Juntang Zhuang, James S. Duncan:
Jointly Discriminative and Generative Recurrent Neural Networks for Learning from fMRI. CoRR abs/1910.06950 (2019) - [i4]Junlin Yang, Nicha C. Dvornek, Fan Zhang, Julius Chapiro, Ming De Lin, Aaron Abajian, James S. Duncan:
Hepatocellular Carcinoma Intra-arterial Treatment Response Prediction for Improved Therapeutic Decision-Making. CoRR abs/1912.00411 (2019) - 2018
- [i3]Nicha C. Dvornek, Daniel Y.-J. Yang, Archana Venkataraman, Pamela Ventola, Lawrence H. Staib, Kevin A. Pelphrey, James S. Duncan:
Prediction of Autism Treatment Response from Baseline fMRI using Random Forests and Tree Bagging. CoRR abs/1805.09799 (2018) - [i2]Xiaoxiao Li, Nicha C. Dvornek, Juntang Zhuang, Pamela Ventola, James S. Duncan:
Brain Biomarker Interpretation in ASD Using Deep Learning and fMRI. CoRR abs/1808.08296 (2018) - [i1]Xiaoxiao Li, Nicha C. Dvornek, Yuan Zhou, Juntang Zhuang, Pamela Ventola, James S. Duncan:
Efficient Interpretation of Deep Learning Models Using Graph Structure and Cooperative Game Theory: Application to ASD Biomarker Discovery. CoRR abs/1812.06181 (2018)
Coauthor Index
[j9] [j4] [j2] [j1] [c41] [c38] [c37] [c36] [c34] [c33] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [c6] [c5] [c4] [c3] [c2] [i34] [i33] [i29] [i27] [i25] [i23] [i22] [i21] [i20] [i18] [i16] [i15] [i13] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [i5] [i4] [i3] [i2] [i1]
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