Last Posted: May 28, 2024
- High-Throughput Genomics Identify Novel FBN1/2 Variants in Severe Neonatal Marfan Syndrome and Congenital Heart Defects.
Gloria K E Zodanu et al. Int J Mol Sci 2024 25(10) - Pulmonary Hypertension Detection Non-Invasively at Point-of-Care Using a Machine-Learned Algorithm.
Navid Nemati et al. Diagnostics (Basel) 2024 14(9) - Echocardiographic artificial intelligence for pulmonary hypertension classification.
Yukina Hirata et al. Heart 2024 - Yield of genetic evaluation in non-syndromic pediatric moyamoya patients.
Anna L Slingerland et al. Childs Nerv Syst 2023 - A transparent artificial intelligence framework to assess lung disease in pulmonary hypertension.
Michail Mamalakis et al. Scientific reports 2023 13(1) 3812 - 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
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Disclaimer: Articles listed in the Public Health Genomics and Precision 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.