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Last Posted: Jun 25, 2024
- Individual Predictors of Response to A Behavioral Activation-Based Digital Smoking Cessation Intervention: A Machine Learning Approach.
Siyuan Huang et al. Subst Use Misuse 2024 1-9 - Assessing fairness in machine learning models: A study of racial bias using matched counterparts in mortality prediction for patients with chronic diseases.
Yifei Wana et al. J Biomed Inform 2024 104677 - Exacerbation predictive modelling using real-world data from the myCOPD app.
Henry M G Glyde et al. Heliyon 2024 10(10) e31201 - Telephone follow-up based on artificial intelligence technology among hypertension patients: Reliability study.
Siyuan Wang et al. J Clin Hypertens (Greenwich) 2024 - Using machine learning to extract information and predict outcomes from reports of randomised trials of smoking cessation interventions in the Human Behaviour-Change Project.
Robert West et al. Wellcome Open Res 2024 8452 - Personalized prediction of diabetic foot ulcer recurrence in elderly individuals using machine learning paradigms.
Shichai Hong et al. Technol Health Care 2024 - Carpal Tunnel Syndrome and Transthyretin Amyloidosis in the All of Us Research Program.
Naman S Shetty et al. Mayo Clin Proc 2024 - An approach to identify gene-environment interactions and reveal new biological insight in complex traits
- A scoping review of web-based, interactive, personalized decision-making tools available to support breast cancer treatment and survivorship care.
Kaitlyn M Wojcik et al. J Cancer Surviv 2024 - A Scoping Review of Personalized, Interactive, Web-Based Clinical Decision Tools Available for Breast Cancer Prevention and Screening in the United States.
Dalya Kamil et al. MDM Policy Pract 2024 9(1) 23814683241236511
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About HLBS-PopOmics
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
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Site Citation:
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
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