Last Posted: Feb 22, 2024
- A Test to Comprehensively Capture the Known Genetic Component of Familial Pulmonary Fibrosis.
Judith Villeneuve et al. Am J Respir Cell Mol Biol 2024 - Developing radiology diagnostic tools for pulmonary fibrosis using machine learning methods.
Weijia Fan et al. Clin Imaging 2023 106110047 - Deep learning diagnostic and severity-stratification for interstitial lung diseases and chronic obstructive pulmonary disease in digital lung auscultations and ultrasonography: clinical protocol for an observational case-control study.
Johan N Siebert et al. BMC Pulm Med 2023 23(1) 191 - Prediction of persistent chronic cough in patients with chronic cough using machine learning.
Wansu Chen et al. ERJ open research 2023 9(2) - Research Progress of Respiratory Disease and Idiopathic Pulmonary Fibrosis Based on Artificial Intelligence.
Gerui Zhang et al. Diagnostics (Basel, Switzerland) 2023 13(3) - European Respiratory Society Statement on Familial Pulmonary Fibrosis.
Borie Raphael et al. The European respiratory journal 2022 - Genetics in Idiopathic Pulmonary Fibrosis: A Clinical Perspective.
Papiris Spyros A et al. Diagnostics (Basel, Switzerland) 2022 12(12) - Deep Learning for Estimating Lung Capacity on Chest Radiographs Predicts Survival in Idiopathic Pulmonary Fibrosis.
Kim Hyungjin et al. Radiology 2022 220292 - The current status and future of FDA-approved artificial intelligence tools in chest radiology in the United States.
Milam M E et al. Clinical radiology 2022 - Screening for idiopathic pulmonary fibrosis using comorbidity signatures in electronic health records.
Onishchenko Dmytro et al. Nature medicine 2022 9
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Disclaimer: Articles listed in the Public Health Genomics and Precision Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.