Differential Diagnosis of Pleural Effusion Using Machine Learning-Reference-Cited by-同舟云学术

Differential Diagnosis of Pleural Effusion Using Machine Learning

Published:2024-02 Issue:2 Volume:21 Page:211-217
ISSN:2329-6933
Container-title:Annals of the American Thoracic Society
language:en
Short-container-title:Annals ATS

Author:

Kim Na Young¹,Jang Boa²³,Gu Kang-Mo⁴,Park Young Sik⁵,Kim Young-Gon²⁶,Cho Jaeyoung⁵⁷^ORCID

Affiliation:

1. Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, Republic of Korea;

2. Department of Transdisciplinary Medicine and

3. Interdisciplinary Program in Bioengineering, College of Engineering, Seoul National University, Seoul, Republic of Korea;

4. Department of Internal Medicine, Chung-Ang University College of Medicine, Seoul, Republic of Korea;

5. Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea;

6. Department of Medicine and

7. Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea

Funder

Seoul National University Hospital Research Fund

Publisher

American Thoracic Society

Subject

Pulmonary and Respiratory Medicine

Link

https://www.atsjournals.org/doi/pdf/10.1513/AnnalsATS.202305-410OC

Reference29 articles.

1. Pleural Disease

2. Investigation of a unilateral pleural effusion in adults: British Thoracic Society pleural disease guideline 2010

3. Tuberculous pleural effusions: increased culture yield with bedside inoculation of pleural fluid and poor diagnostic value of adenosine deaminase.

4. Tuberculous pleural effusion

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1. Man versus Machine in Pleural Diagnostics: Does Artificial Intelligence Provide the Solution?;Annals of the American Thoracic Society;2024-02