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03/18/2023
Report of the Medical Image De-Identification (MIDI) Task Group – Best Practices and Recommendations
This report addresses the technical aspects of de-identification of medi...
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07/31/2022
Augmenting Vision Language Pretraining by Learning Codebook with Visual Semantics
Language modality within the vision language pretraining framework is in...
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04/16/2022
Few-Shot Transfer Learning to improve Chest X-Ray pathology detection using limited triplets
Deep learning approaches applied to medical imaging have reached near-hu...
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04/06/2022
OSCARS: An Outlier-Sensitive Content-Based Radiography Retrieval System
Improving the retrieval relevance on noisy datasets is an emerging need ...
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02/03/2022
Best Practices and Scoring System on Reviewing A.I. based Medical Imaging Papers: Part 1 Classification
With the recent advances in A.I. methodologies and their application to ...
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12/27/2021
MedShift: identifying shift data for medical dataset curation
To curate a high-quality dataset, identifying data variance between the ...
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10/29/2021
CVAD: A generic medical anomaly detector based on Cascade VAE
Detecting out-of-distribution (OOD) samples in medical imaging plays an ...
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07/31/2021
Margin-Aware Intra-Class Novelty Identification for Medical Images
Traditional anomaly detection methods focus on detecting inter-class var...
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06/03/2021
A Prospective Observational Study to Investigate Performance of a Chest X-ray Artificial Intelligence Diagnostic Support Tool Across 12 U.S. Hospitals
Importance: An artificial intelligence (AI)-based model to predict COVID...
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07/11/2020
Generalization of Deep Convolutional Neural Networks – A Case-study on Open-source Chest Radiographs
Deep Convolutional Neural Networks (DCNNs) have attracted extensive atte...
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05/20/2020
Artificial Intelligence for Global Health: Learning From a Decade of Digital Transformation in Health Care
The health needs of those living in resource-limited settings are a vast...
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04/16/2020