Chronic Obstructive Pulmonary Disease
Last Posted: Feb 20, 2024
- A machine learning model for predicting acute exacerbation of in-home chronic obstructive pulmonary disease patients.
Huiming Yin et al. Comput Methods Programs Biomed 2024 246108005
- A novel risk score predicting 30-day hospital re-admission of patients with acute stroke by machine learning model.
Giovanna Mercurio et al. Eur J Neurol 2023
- Machine learning for the development of diagnostic models of decompensated heart failure or exacerbation of chronic obstructive pulmonary disease.
César Gálvez-Barrón et al. Sci Rep 2023 13(1) 12709
- Using random forest machine learning on data from a large, representative cohort of the general population improves clinical spirometry references.
Kris Kristensen et al. Clin Respir J 2023
- Experimental drugs in clinical trials for COPD: Artificial Intelligence via Machine Learning approach to predict the successful advance from early-stage development to approval.
Luigino Calzetta et al. Expert Opin Investig Drugs 2023
- A new diagnostic method for chronic obstructive pulmonary disease using the photoplethysmography signal and hybrid artificial intelligence.
Engin Melekoglu et al. PeerJ Comput Sci 2023 8e1188
- 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
- Machine learning for screening of at-risk, mild and moderate COPD patients at risk of FEV decline: results from COPDGene and SPIROMICS.
Jennifer M Wang et al. Front Physiol 2023 141144192
- Deep learning model improves COPD risk prediction and gene discovery.
et al. Nat Genet 2023 4
- Inference of chronic obstructive pulmonary disease with deep learning on raw spirograms identifies new genetic loci and improves risk models.
Justin Cosentino et al. Nat Genet 2023 4
HLBS-PopOmics is an online, continuously updated, searchable database of published scientific literature, CDC and NIH resources, and other materials that address the translation of genomic and other precision health discoveries into improved health care and prevention related to Heart and Vascular Diseases(H), Lung Diseases(L), Blood Diseases(B), and Sleep Disorders(S)...more
Mensah GA, Yu W, Barfield WL, Clyne M, Engelgau MM, Khoury MJ. HLBS-PopOmics: an online knowledge base to accelerate dissemination and implementation of research advances in population genomics to reduce the burden of heart, lung, blood, and sleep disorders. Genet Med. 2018 Sep 10. doi: 10.1038/s41436-018-0118-1
Disclaimer: Articles listed in the Public Health Knowledge Base are selected by Public Health Genomics Branch 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.
- Page last reviewed:Feb 1, 2024
- Page last updated:Feb 23, 2024
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