Paul H. Yi

Orcid: 0000-0001-9433-8093

According to our database1, Paul H. Yi authored at least 17 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Anytime, Anywhere, Anyone: Investigating the Feasibility of Segment Anything Model for Crowd-Sourcing Medical Image Annotations.
CoRR, 2024

Out-of-Distribution Detection and Data Drift Monitoring using Statistical Process Control.
CoRR, 2024

Hidden in Plain Sight: Undetectable Adversarial Bias Attacks on Vulnerable Patient Populations.
CoRR, 2024

2023
One Copy Is All You Need: Resource-Efficient Streaming of Medical Imaging Data at Scale.
CoRR, 2023

High-Throughput AI Inference for Medical Image Classification and Segmentation using Intelligent Streaming.
CoRR, 2023

Text2Cohort: Democratizing the NCI Imaging Data Commons with Natural Language Cohort Discovery.
CoRR, 2023

Optimizing Federated Learning for Medical Image Classification on Distributed Non-iid Datasets with Partial Labels.
CoRR, 2023

SegViz: A Federated Learning Framework for Medical Image Segmentation from Distributed Datasets with Different and Incomplete Annotations.
CoRR, 2023

Surgical Aggregation: A Federated Learning Framework for Harmonizing Distributed Datasets with Diverse Tasks.
CoRR, 2023

Estimating and Controlling for Equalized Odds via Sensitive Attribute Predictors.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Machine vs. Radiologist-Based Translations of RadLex: Implications for Multi-language Report Interoperability.
J. Digit. Imaging, 2022

Weakly Supervised Learning Significantly Reduces the Number of Labels Required for Intracranial Hemorrhage Detection on Head CT.
CoRR, 2022

From Competition to Collaboration: Making Toy Datasets on Kaggle Clinically Useful for Chest X-Ray Diagnosis Using Federated Learning.
CoRR, 2022

Estimating and Controlling for Fairness via Sensitive Attribute Predictors.
CoRR, 2022

2021
DeepCAT: Deep Computer-Aided Triage of Screening Mammography.
J. Digit. Imaging, 2021

2019
Deep-Learning-Based Semantic Labeling for 2D Mammography and Comparison of Complexity for Machine Learning Tasks.
J. Digit. Imaging, 2019

Deep Learning Method for Automated Classification of Anteroposterior and Posteroanterior Chest Radiographs.
J. Digit. Imaging, 2019


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