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Paul H. Yi
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2020 – today
- 2024
- [j5]Stephanie L. McNamara, Paul H. Yi, William Lotter:
The clinician-AI interface: intended use and explainability in FDA-cleared AI devices for medical image interpretation. npj Digit. Medicine 7(1) (2024) - [c2]Adway U. Kanhere, Pranav Kulkarni, Paul H. Yi, Vishwa S. Parekh:
Privacy-Preserving Collaboration for Multi-Organ Segmentation via Federated Learning from Sites with Partial Labels. CVPR Workshops 2024: 2380-2387 - [i15]Pranav Kulkarni, Andrew Chan, Nithya Navarathna, Skylar Chan, Paul H. Yi, Vishwa S. Parekh:
Hidden in Plain Sight: Undetectable Adversarial Bias Attacks on Vulnerable Patient Populations. CoRR abs/2402.05713 (2024) - [i14]Ghada Zamzmi, Kesavan Venkatesh, Brandon Nelson, Smriti Prathapan, Paul H. Yi, Berkman Sahiner, Jana G. Delfino:
Out-of-Distribution Detection and Data Drift Monitoring using Statistical Process Control. CoRR abs/2402.08088 (2024) - [i13]Pranav Kulkarni, Adway U. Kanhere, Dharmam Savani, Andrew Chan, Devina Chatterjee, Paul H. Yi, Vishwa S. Parekh:
Anytime, Anywhere, Anyone: Investigating the Feasibility of Segment Anything Model for Crowd-Sourcing Medical Image Annotations. CoRR abs/2403.15218 (2024) - [i12]Pranav Kulkarni, Adway U. Kanhere, Harshita Kukreja, Vivian Zhang, Paul H. Yi, Vishwa S. Parekh:
Improving Multi-Center Generalizability of GAN-Based Fat Suppression using Federated Learning. CoRR abs/2404.07374 (2024) - [i11]Skylar Chan, Pranav Kulkarni, Paul H. Yi, Vishwa S. Parekh:
Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray Classification. CoRR abs/2405.00156 (2024) - [i10]Beepul Bharti, Paul H. Yi, Jeremias Sulam:
Sufficient and Necessary Explanations (and What Lies in Between). CoRR abs/2409.20427 (2024) - 2023
- [c1]Beepul Bharti, Paul H. Yi, Jeremias Sulam:
Estimating and Controlling for Equalized Odds via Sensitive Attribute Predictors. NeurIPS 2023 - [i9]Pranav Kulkarni, Adway U. Kanhere, Paul H. Yi, Vishwa S. Parekh:
Surgical Aggregation: A Federated Learning Framework for Harmonizing Distributed Datasets with Diverse Tasks. CoRR abs/2301.06683 (2023) - [i8]Adway U. Kanhere, Pranav Kulkarni, Paul H. Yi, Vishwa S. Parekh:
SegViz: A Federated Learning Framework for Medical Image Segmentation from Distributed Datasets with Different and Incomplete Annotations. CoRR abs/2301.07074 (2023) - [i7]Pranav Kulkarni, Adway U. Kanhere, Paul H. Yi, Vishwa S. Parekh:
Optimizing Federated Learning for Medical Image Classification on Distributed Non-iid Datasets with Partial Labels. CoRR abs/2303.06180 (2023) - [i6]Pranav Kulkarni, Adway U. Kanhere, Paul H. Yi, Vishwa S. Parekh:
Text2Cohort: Democratizing the NCI Imaging Data Commons with Natural Language Cohort Discovery. CoRR abs/2305.07637 (2023) - [i5]Pranav Kulkarni, Sean Garin, Adway U. Kanhere, Eliot Siegel, Paul H. Yi, Vishwa S. Parekh:
High-Throughput AI Inference for Medical Image Classification and Segmentation using Intelligent Streaming. CoRR abs/2305.15617 (2023) - [i4]Pranav Kulkarni, Adway U. Kanhere, Eliot Siegel, Paul H. Yi, Vishwa S. Parekh:
One Copy Is All You Need: Resource-Efficient Streaming of Medical Imaging Data at Scale. CoRR abs/2307.00438 (2023) - 2022
- [j4]Christian J. Park, Paul H. Yi, Hussain Al Yousif, Kenneth C. Wang:
Machine vs. Radiologist-Based Translations of RadLex: Implications for Multi-language Report Interoperability. J. Digit. Imaging 35(3): 660-665 (2022) - [i3]Beepul Bharti, Paul H. Yi, Jeremias Sulam:
Estimating and Controlling for Fairness via Sensitive Attribute Predictors. CoRR abs/2207.12497 (2022) - [i2]Pranav Kulkarni, Adway U. Kanhere, Paul H. Yi, Vishwa S. Parekh:
From Competition to Collaboration: Making Toy Datasets on Kaggle Clinically Useful for Chest X-Ray Diagnosis Using Federated Learning. CoRR abs/2211.06212 (2022) - [i1]Jacopo Teneggi, Paul H. Yi, Jeremias Sulam:
Weakly Supervised Learning Significantly Reduces the Number of Labels Required for Intracranial Hemorrhage Detection on Head CT. CoRR abs/2211.15924 (2022) - 2021
- [j3]Paul H. Yi, Dhananjay Singh, Susan C. Harvey, Gregory D. Hager, Lisa A. Mullen:
DeepCAT: Deep Computer-Aided Triage of Screening Mammography. J. Digit. Imaging 34(1): 27-35 (2021)
2010 – 2019
- 2019
- [j2]Paul H. Yi, Abigail Lin, Jinchi Wei, Alice C. Yu, Haris I. Sair, Ferdinand K. Hui, Gregory D. Hager, Susan C. Harvey:
Deep-Learning-Based Semantic Labeling for 2D Mammography and Comparison of Complexity for Machine Learning Tasks. J. Digit. Imaging 32(4): 565-570 (2019) - [j1]Tae Kyung Kim, Paul H. Yi, Jinchi Wei, Ji Won Shin, Gregory D. Hager, Ferdinand K. Hui, Haris I. Sair, Cheng Ting Lin:
Deep Learning Method for Automated Classification of Anteroposterior and Posteroanterior Chest Radiographs. J. Digit. Imaging 32(6): 925-930 (2019)
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