Using Artificial Intelligence Software for Diagnosing Emphysema and Interstitial Lung Disease-Reference-Cited by-同舟云学术

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Using Artificial Intelligence Software for Diagnosing Emphysema and Interstitial Lung Disease

Published:2024 Issue:4 Volume:85 Page:714
ISSN:2951-0805
Container-title:Journal of the Korean Society of Radiology
language:ko
Short-container-title:J Korean Soc Radiol

Author:

Paik Sang Hyun¹^ORCID,Jin Gong Yong²^ORCID

Affiliation:

1. Department of Chest, Korea Teleradiology Reading Center, Seoul, Korea.

2. Department of Radiology, Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonbuk National University and Medical School, Jeonju, Korea.

Publisher

XMLink

Link

https://jksronline.org/pdf/10.3348/jksr.2024.0050

Reference25 articles.

1. Fleischner Society Visual Emphysema CT Patterns Help Predict Progression of Emphysema in Current and Former Smokers: Results from the COPDGene Study

2. Deep Learning Assessment of Emphysema Progression at CT Predicts Outcomes

3. Deep Learning Enables Automatic Classification of Emphysema Pattern at CT

4. Artificial Intelligence and Interstitial Lung Disease

5. Deep Learning–based Fibrosis Extent on Computed Tomography Predicts Outcome of Fibrosing Interstitial Lung Disease Independent of Visually Assessed Computed Tomography Pattern

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