Towards Fair Medical AI: Adversarial Debiasing of 3D CT Foundation Embeddings. - Zheng, Guangyao; Jacobs, Michael A.; Braverman, Vladimir; Parekh, Vishwa S. (CoRR, 2025)

A collective AI via lifelong learning and sharing at the edge. - Soltoggio, Andrea; Ben-Iwhiwhu, Eseoghene; Braverman, Vladimir; Eaton, Eric; Epstein, Benjamin; Ge, Yunhao; Halperin, Lucy; How, Jonathan P.; Itti, Laurent; Jacobs, Michael A.; Kantharaju, Pavan; Le, Long; et al. (Nat. Mac. Intell., 2024)

Privacy-Preserving Collaboration for Multi-Organ Segmentation via Federated Learning from Sites with Partial Labels. - Kanhere, Adway U.; Kulkarni, Pranav; Yi, Paul H.; Parekh, Vishwa S. (2024)

Hidden in Plain Sight: Undetectable Adversarial Bias Attacks on Vulnerable Patient Populations. - Kulkarni, Pranav; Chan, Andrew; Navarathna, Nithya; Chan, Skylar; Yi, Paul H.; Parekh, Vishwa Sanjay (2024)

Towards a Collective Medical Imaging AI: Enabling Continual Learning from Peers. - Zheng, Guangyao; Braverman, Vladimir; Leal, Jeffrey; Rowe, Steven; Leung, Doris G.; Jacobs, Michael A.; Parekh, Vishwa Sanjay (2024)

Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray Classification. - Chan, Skylar; Kulkarni, Pranav; Yi, Paul H.; Parekh, Vishwa S. (2024)

Hidden in Plain Sight: Undetectable Adversarial Bias Attacks on Vulnerable Patient Populations. - Kulkarni, Pranav; Chan, Andrew; Navarathna, Nithya; Chan, Skylar; Yi, Paul H.; Parekh, Vishwa S. (CoRR, 2024)

Anytime, Anywhere, Anyone: Investigating the Feasibility of Segment Anything Model for Crowd-Sourcing Medical Image Annotations. - Kulkarni, Pranav; Kanhere, Adway U.; Savani, Dharmam; Chan, Andrew; Chatterjee, Devina; Yi, Paul H.; Parekh, Vishwa S. (CoRR, 2024)

Improving Multi-Center Generalizability of GAN-Based Fat Suppression using Federated Learning. - Kulkarni, Pranav; Kanhere, Adway U.; Kukreja, Harshita; Zhang, Vivian; Yi, Paul H.; Parekh, Vishwa S. (CoRR, 2024)

Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray Classification. - Chan, Skylar; Kulkarni, Pranav; Yi, Paul H.; Parekh, Vishwa S. (CoRR, 2024)

Demographic Predictability in 3D CT Foundation Embeddings. - Zheng, Guangyao; Jacobs, Michael A.; Parekh, Vishwa S. (CoRR, 2024)

Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging. - Zheng, Guangyao; Zhou, Samson; Braverman, Vladimir; Jacobs, Michael A.; Parekh, Vishwa Sanjay (2023)

Surgical Aggregation: A Federated Learning Framework for Harmonizing Distributed Datasets with Diverse Tasks. - Kulkarni, Pranav; Kanhere, Adway U.; Yi, Paul H.; Parekh, Vishwa S. (CoRR, 2023)

SegViz: A Federated Learning Framework for Medical Image Segmentation from Distributed Datasets with Different and Incomplete Annotations. - Kanhere, Adway U.; Kulkarni, Pranav; Yi, Paul H.; Parekh, Vishwa S. (CoRR, 2023)

Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging. - Zheng, Guangyao; Zhou, Samson; Braverman, Vladimir; Jacobs, Michael A.; Parekh, Vishwa S. (CoRR, 2023)

Optimizing Federated Learning for Medical Image Classification on Distributed Non-iid Datasets with Partial Labels. - Kulkarni, Pranav; Kanhere, Adway U.; Yi, Paul H.; Parekh, Vishwa S. (CoRR, 2023)

Asynchronous Decentralized Federated Lifelong Learning for Landmark Localization in Medical Imaging. - Zheng, Guangyao; Jacobs, Michael A.; Braverman, Vladimir; Parekh, Vishwa S. (CoRR, 2023)

Text2Cohort: Democratizing the NCI Imaging Data Commons with Natural Language Cohort Discovery. - Kulkarni, Pranav; Kanhere, Adway U.; Yi, Paul H.; Parekh, Vishwa S. (CoRR, 2023)

High-Throughput AI Inference for Medical Image Classification and Segmentation using Intelligent Streaming. - Kulkarni, Pranav; Garin, Sean; Kanhere, Adway U.; Siegel, Eliot; Yi, Paul H.; Parekh, Vishwa S. (CoRR, 2023)

Multi-environment lifelong deep reinforcement learning for medical imaging. - Zheng, Guangyao; Lai, Shuhao; Braverman, Vladimir; Jacobs, Michael A.; Parekh, Vishwa S. (CoRR, 2023)

A framework for dynamically training and adapting deep reinforcement learning models to different, low-compute, and continuously changing radiology deployment environments. - Zheng, Guangyao; Lai, Shuhao; Braverman, Vladimir; Jacobs, Michael A.; Parekh, Vishwa S. (CoRR, 2023)

One Copy Is All You Need: Resource-Efficient Streaming of Medical Imaging Data at Scale. - Kulkarni, Pranav; Kanhere, Adway U.; Siegel, Eliot; Yi, Paul H.; Parekh, Vishwa S. (CoRR, 2023)

From Competition to Collaboration: Making Toy Datasets on Kaggle Clinically Useful for Chest X-Ray Diagnosis Using Federated Learning. - Kulkarni, Pranav; Kanhere, Adway U.; Yi, Paul H.; Parekh, Vishwa S. (CoRR, 2022)

Cross-Domain Federated Learning in Medical Imaging. - Parekh, Vishwa S.; Lai, Shuhao; Braverman, Vladimir; Leal, Jeff; Rowe, Steven; Pillai, Jay J.; Jacobs, Michael A. (CoRR, 2021)

Multitask radiological modality invariant landmark localization using deep reinforcement learning. - Parekh, Vishwa S.; Bocchieri, Alex E.; Braverman, Vladimir; Jacobs, Michael A. (2020)

Radiomic Synthesis Using Deep Convolutional Neural Networks. - Parekh, Vishwa S.; Jacobs, Michael A. (2019)

Tumor Connectomics: Mapping the intra-tumoral complex interaction network. - Parekh, Vishwa S.; Jacobs, Michael A. (CoRR, 2019)

Multiparametric Deep Learning and Radiomics for Tumor Grading and Treatment Response Assessment of Brain Cancer: Preliminary Results. - Parekh, Vishwa S.; Laterra, John; Bettegowda, Chetan; Bocchieri, Alex E.; Pillai, Jay J.; Jacobs, Michael A. (CoRR, 2019)

Multiparametric Deep Learning Tissue Signatures for Muscular Dystrophy: Preliminary Results. - Bocchieri, Alex E.; Parekh, Vishwa S.; Wagner, Kathryn R.; Ahlawat, Shivani; Braverman, Vladimir; Leung, Doris G.; Jacobs, Michael A. (CoRR, 2019)

Multiparametric Deep Learning Tissue Signatures for a Radiological Biomarker of Breast Cancer: Preliminary Results. - Parekh, Vishwa S.; Macura, Katarzyna J.; Harvey, Susan C.; Kamel, Ihab; Khouli, Riham El; Bluemke, David A.; Jacobs, Michael A. (CoRR, 2018)

MPRAD: A Multiparametric Radiomics Framework. - Parekh, Vishwa S.; Jacobs, Michael A. (CoRR, 2018)

Radiomic Synthesis Using Deep Convolutional Neural Networks. - Parekh, Vishwa S.; Jacobs, Michael A. (CoRR, 2018)

Advanced machine learning informatics modeling using clinical and radiological imaging metrics for characterizing breast tumor characteristics with the OncotypeDX gene array. - Jacobs, Michael A.; Umbricht, Christopher; Parekh, Vishwa S.; Khouli, Riham El; Cope, Leslie; Macura, Katarzyna J.; Harvey, Susan C.; Wolff, Antonio C. (CoRR, 2018)

A multidimensional data visualization and clustering method: Consensus similarity mapping. - Parekh, Vishwa S.; Jacobs, Michael A. (2016)

Unsupervised Non Linear Dimensionality Reduction Machine Learning methods applied to Multiparametric MRI in cerebral ischemia: Preliminary Results. - Parekh, Vishwa S.; Jacobs, Jeremy R.; Jacobs, Michael A. (CoRR, 2016)

Unsupervised nonlinear dimensionality reduction machine learning methods applied to multiparametric MRI in cerebral ischemia: preliminary results. - Parekh, Vishwa S.; Jacobs, Jeremy R.; Jacobs, Michael A. (2014)