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Last Posted: Dec 21, 2020
- Chest x-ray analysis with deep learning-based software as a triage test for pulmonary tuberculosis: a prospective study of diagnostic accuracy for culture-confirmed disease.
Khan Faiz Ahmad et al. The Lancet. Digital health 2020 Nov 2(11) e573-e581 - Effect of family history, occupation and diet on the risk of Parkinson disease: A case-control study.
Torti Margherita et al. PloS one 2020 15(12) e0243612 - Inequalities and risk factors related to non-participation in colorectal cancer screening programmes: a systematic review.
Unanue-Arza Saloa et al. European journal of public health 2020 Dec - Machine-learning-based prediction models for high-need high-cost patients using nationwide clinical and claims data.
Osawa Itsuki et al. NPJ digital medicine 2020 Nov 3(1) 148 - Prognostic Value of EZH2 in Non-Small-Cell Lung Cancers: A Meta-Analysis and Bioinformatics Analysis.
Fan Kui et al. BioMed research international 2020 20202380124 - Transferability Of Ancestry-Specific And Cross-Ancestry CYP2A6 Activity Genetic Risk Scores In African And European Populations.
El-Boraie Ahmed et al. Clinical pharmacology and therapeutics 2020 Dec - Acceptability and potential impact on uptake of using different risk stratification approaches to determine eligibility for screening: A population-based survey.
Usher-Smith Juliet A et al. Health expectations : an international journal of public participation in health care and health policy 2020 Dec - The Relationships Between Prenatal Smoking Exposure and Telomere Lengths in Fetuses, Infants, and Children: A Systematic Literature Review.
Wei Holly et al. Journal of addictions nursing 31(4) 243-252 - Evaluation of incomplete maternal smoking data using machine learning algorithms: a study from the Medical Birth Registry of Norway.
Grøtvedt Liv et al. BMC pregnancy and childbirth 2020 Nov 20(1) 710 - Prediction of metabolic syndrome based on sleep and work-related risk factors using an artificial neural network.
Eyvazlou Meysam et al. BMC endocrine disorders 2020 Nov 20(1) 169 - Educational attainment reduces the risk of suicide attempt among individuals with and without psychiatric disorders independent of cognition: a bidirectional and multivariable Mendelian randomization study with more than 815,000 participants.
Rosoff Daniel B et al. Translational psychiatry 2020 Nov 10(1) 388 - Familial Hypercholesterolemia in Premature Acute Coronary Syndrome. Insights from CholeSTEMI Registry.
Lorca Rebeca et al. Journal of clinical medicine 2020 Oct 9(11) - The therapeutic management of South African dyslipidaemic patients at very high cardiovascular risk (CARDIO TRACK): a cross-sectional study.
Blom Dirk Jacobus et al. Cardiovascular journal of Africa 31(5) 245-251 - A simple, rapid, interpretable, actionable and implementable digital PCR based mortality index.
Philibert Robert et al. Epigenetics 2020 Nov 1-15 - Cohort profile: CROSS-TRACKS: a population-based open cohort across healthcare sectors in Denmark.
Riis Anders Hammerich et al. BMJ open 2020 Oct 10(10) e039996
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 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
Content Summary
- CDC Information (26)
- NIH Information (21)
- COVID-19 (150)
- CDC Publications (4)
- Human Genome Epidemiologic Studies (8034)
- GWAS Studies (163)
- Human Genomics Translation/Implementation Studies (254)
- Genomic Tests Evidence Synthesis (48)
- Genomic Tests Guidelines (8)
- Tier-Classified Guidelines (2)
- Non-Genomics Precision Health (64)
- State Public Health Genomics Programs (31)
- Reviews/Commentaries (149)
- Tools/Methods (3)
Common HLBS Health Categories
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 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:Oct 1, 2020
- Page last updated:Dec 28, 2020
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