Last Posted: Apr 12, 2022
- Lung Transplantation Advanced Prediction Tool: Determining Recipient's Outcome for a Certain Donor.
Zafar Farhan et al. Transplantation 2022
- Development and evaluation of a predictive algorithm for unsatisfactory response among patients with pulmonary arterial hypertension using health insurance claims data.
Gauthier-Loiselle Marjolaine et al. Current medical research and opinion 2022 1-33
- A Framework for Using Real-World Data and Health Outcomes Modeling to Evaluate Machine Learning-Based Risk Prediction Models.
Rodriguez Patricia J et al. Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research 2022 25(3) 350-358
- Three Doses of an mRNA Covid-19 Vaccine in Solid-Organ Transplant Recipients.
Kamar Nassim et al. The New England journal of medicine 2021 6
- Developing a Decision Aid to Facilitate Informed Decision Making About Invasive Mechanical Ventilation and Lung Transplantation Among Adults With Cystic Fibrosis: Usability Testing.
Dauber-Decker Katherine L et al. JMIR human factors 2021 8(2) e21270
- Machine learning can predict disease manifestations and outcomes in lymphangioleiomyomatosis.
Chernbumroong Saisakul et al. The European respiratory journal 2020 Dec
- Detecting Acute Cellular Rejection in Lung Transplant Biopsies by Artificial Intelligence: A Novel Deep Learning Approach.
Davis H et al. The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation 2020 Apr 39(4S) S501-S502
- Investigating the use of data-driven artificial intelligence in computerised decision support systems for health and social care: A systematic review.
Cresswell Kathrin et al. Health informatics journal 2020 Jan 1460458219900452
- Whole Blood Gene Expression Profiling Predicts Severe Morbidity and Mortality in Cystic Fibrosis: A 5-Year Follow-Up Study.
Saavedra Milene T et al. Annals of the American Thoracic Society 2018 15(5) 589-598
- [Selection of lung transplant candidates in France in 2019].
Falque L et al. Revue des maladies respiratoires 2019 Apr 36(4) 508-518
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 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.