Last Posted: Dec 30, 2022
- Professional expectations and patient expectations concerning the development of Artificial Intelligence (AI) for the early diagnosis of Pulmonary Hypertension (PH).
Winter Peter et al. Journal of responsible technology 2022 12None
- Genetic Analysis of Cardiac Syncope-Related Genes in Korean Patients with Recurrent Neurally Mediated Syncope.
Lee Sung Ho et al. Journal of cardiovascular development and disease 2022 9(8)
- Validation of Artificial Intelligence Cardiac MRI Measurements: Relationship to Heart Catheterization and Mortality Prediction.
Alabed Samer et al. Radiology 2022 212929
- (De)troubling transparency: artificial intelligence (AI) for clinical applications.
Winter Peter David et al. Medical humanities 2022
- Invited editorial: Q and A on hereditary lung cancer.
Benusiglio Patrick R et al. Respiratory medicine and research 2022 81100881
- Training and clinical testing of artificial intelligence derived right atrial cardiovascular magnetic resonance measurements.
Alandejani Faisal et al. Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance 2022 24(1) 25
- Risk prediction in pulmonary hypertension due to chronic heart failure: incremental prognostic value of pulmonary hemodynamics.
Quan Ruilin et al. BMC cardiovascular disorders 2022 22(1) 56
- Evidence Used to Update the List of Underlying Medical Conditions Associated with Higher Risk for Severe COVID-19
CDC Science Brief, October 14, 2021
- Genetics of diaphragmatic hernia.
Schreiner Yannick et al. European journal of human genetics : EJHG 2021
- Diagnostic test accuracy of artificial intelligence analysis of cross-sectional imaging in pulmonary hypertension: a systematic literature review.
Hardacre Conor Joseph et al. The British journal of radiology 2021 20210332
- Evaluation of Effect of Curcumin on Psychological State of Patients with Pulmonary Hypertension by Magnetic Resonance Image under Deep Learning.
Ma Tingting et al. Contrast media & molecular imaging 2021 20219935754
- Radiomics side experiments and DAFIT approach in identifying pulmonary hypertension using Cardiac MRI derived radiomics based machine learning models.
Priya Sarv et al. Scientific reports 2021 11(1) 12686
- Radiomics Detection of Pulmonary Hypertension via Texture-Based Assessments of Cardiac MRI: A Machine-Learning Model Comparison-Cardiac MRI Radiomics in Pulmonary Hypertension.
Priya Sarv et al. Journal of clinical medicine 2021 10(9)
- United States Pulmonary Hypertension Scientific Registry (USPHSR): Baseline Characteristics.
Badlam Jessica B et al. Chest 2020 Aug
- Machine learning for the diagnosis of pulmonary hypertension.
Zhu Fubao et al. Kardiologiia 2020 Jul 60(6) 953
- Machine Learning and Deep Neural Network Applications in the Thorax: Pulmonary Embolism, Chronic Thromboembolic Pulmonary Hypertension, Aorta, and Chronic Obstructive Pulmonary Disease.
Remy-Jardin Martine et al. Journal of thoracic imaging 2020 Apr
- Molecular genetic framework underlying pulmonary arterial hypertension.
Southgate Laura et al. Nature reviews. Cardiology 2019 Aug
- Precision medicine: The future of diagnostic approach to pulmonary hypertension?
Kedzierski Piotr et al. Anatolian journal of cardiology 2019 Sep (4) 168-171
- Definition, clinical classification and initial diagnosis of pulmonary hypertension: Updated recommendations from the Cologne Consensus Conference 2018.
Kovacs Gabor et al. International journal of cardiology 2018 Dec 272S11-19
- [Heterogeneous phenotypes, genotypes, treatment and prevention of 1 003 patients with methylmalonic acidemia in the mainland of China].
Liu Y et al. Zhonghua er ke za zhi = Chinese journal of pediatrics 2018 Jun 56(6) 414-420
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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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.