Chronic Obstructive Pulmonary Disease
Last Posted: May 09, 2023
- 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
- Modelling 30-day hospital readmission after discharge for COPD patients based on electronic health records.
Meng Li et al. NPJ Prim Care Respir Med 2023 33(1) 16
- Estimating individual treatment effects on COPD exacerbations by causal machine learning on randomised controlled trials.
Kenneth Verstraete et al. Thorax 2023
- Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk.
Nick Shrine et al. Nature genetics 2023 3 (3) 410-422
- Development and validation of a respiratory-responsive vocal biomarker-based tool for generalizable detection of respiratory impairment: independent case-control studies in multiple respiratory conditions including asthma, chronic obstructive pulmonary disease, and COVID-19.
Savneet Kaur et al. Journal of medical Internet research 2023
- Intercontinental validation of a clinical prediction model for predicting 90-day and 2-year mortality in an Israeli cohort of 2033 patients with a femoral neck fracture aged 65 or above.
Jacobien H F Oosterhoff et al. European journal of trauma and emergency surgery : official publication of the European Trauma Society 2023
- Prediction of short-term atrial fibrillation risk using primary care electronic health records.
Ramesh Nadarajah et al. Heart (British Cardiac Society) 2023
- Diagnostic performance of a machine-learning algorithm (Asthma/COPD Differentiation Classification; AC/DC) tool versus primary care physicians and pulmonologists in asthma, COPD and ACO.
Janwillem W H Kocks et al. The journal of allergy and clinical immunology. In practice 2023
- Machine learning-enabled risk prediction of chronic obstructive pulmonary disease with unbalanced data.
Wang Xuchun et al. Computer methods and programs in biomedicine 2023 230107340
- Artificial Intelligence Analysis of Bronchiectasis Is Predictive of Outcomes in Chronic Obstructive Pulmonary Disease.
Schiebler Mark L et al. Radiology 2022 222675
- Using genomic profiling for understanding and improving response to smoking cessation treatment.
Bierut Laura J et al. Current epidemiology reports 2022 6(4) 486-490
- Community determinants of COPD exacerbations in elderly patients in Lodz province, Poland: a retrospective observational Big Data cohort study.
Kowalczyk Anna et al. BMJ open 2022 12(10) e060247
- Artificial intelligence to differentiate asthma from COPD in medico-administrative databases.
Joumaa Hassan et al. BMC pulmonary medicine 2022 22(1) 357
- Prediction of COPD acute exacerbation in response to air pollution using exosomal circRNA profile and Machine learning.
Meng Qingtao et al. Environment international 2022 168107469
- [Quantitative Evaluation of Airway Lesions in Chronic Obstructive Pulmonary Disease by Applying Deep Learning Reconstruction to Ultra-high-resolution CT Images: Correlation between Wall Area Percentage and Forced Expiratory Volume in One Second Percentage].
Muramatsu Shun et al. Nihon Hoshasen Gijutsu Gakkai zasshi 2022
- Predictive modeling of COPD exacerbation rates using baseline risk factors.
Singh Dave et al. Therapeutic advances in respiratory disease 2022 1617534666221107314
- A New Random Forest Algorithm-Based Prediction Model of Post-operative Mortality in Geriatric Patients With Hip Fractures.
Xing Fei et al. Frontiers in medicine 2022 9829977
- Predicting 30-Day Readmission Risk for Patients With Chronic Obstructive Pulmonary Disease Through a Federated Machine Learning Architecture on Findable, Accessible, Interoperable, and Reusable (FAIR) Data: Development and Validation Study.
Alvarez-Romero Celia et al. JMIR medical informatics 2022 10(6) e35307
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
Common HLBS Health Categories
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 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.
- Page last reviewed:Feb 1, 2023
- Page last updated:May 31, 2023
- Content source: