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Last Posted: Nov 28, 2023
- Development and Evaluation of a Natural Language Processing System for Curating a Trans-Thoracic Echocardiogram (TTE) Database.
Tim Dong et al. Bioengineering (Basel) 2023 10(11) - Improved assessment of left ventricular ejection fraction using artificial intelligence in echocardiography: A comparative analysis with cardiac magnetic resonance imaging.
Krunoslav Michael Sveric et al. Int J Cardiol 2023 131383 - Artificial intelligence in the pediatric echocardiography laboratory: Automation, physiology, and outcomes.
Minh B Nguyen et al. Front Radiol 2023 2881777 - Development and validation of echocardiography-based machine-learning models to predict mortality.
Akshay Valsaraj et al. EBioMedicine 2023 90104479 - Deep-Learning Models for Detection and Localization of Visible Clinically Significant Prostate Cancer on Multi-Parametric MRI.
Zhaonan Sun et al. Journal of magnetic resonance imaging : JMRI 2023 - Multi-center retrospective cohort study applying deep learning to electrocardiograms to identify left heart valvular dysfunction
A Vaid et al, Comm Med, February 14, 2023 - Addressing disparities in pharmacogenomics through rural and underserved workforce education.
Jacob T Brown et al. Frontiers in genetics 2023 131082985 - Automated MR Image Prescription of the Liver Using Deep Learning: Development, Evaluation, and Prospective Implementation.
Geng Ruiqi et al. Journal of magnetic resonance imaging : JMRI 2022 - Value of Artificial Neural Network Ultrasound in Improving Breast Cancer Diagnosis.
Chai Qiaolian et al. Computational intelligence and neuroscience 2022 20221779337 - Therapeutic thoroughfares for adults living with Pompe disease.
Schoser Benedikt et al. Current opinion in neurology 2022 - Feasibility and Impact of Integrating an Artificial Intelligence-Based Diagnosis Aid for Autism Into the Extension for Community Health Outcomes Autism Primary Care Model: Protocol for a Prospective Observational Study.
Sohl Kristin et al. JMIR research protocols 2022 11(7) e37576 - Machine Learning Based on MRI DWI Radiomics Features for Prognostic Prediction in Nasopharyngeal Carcinoma.
Hu Qiyi et al. Cancers 2022 14(13) - Fully Automated MRI Segmentation and Volumetric Measurement of Intracranial Meningioma Using Deep Learning.
Kang Ho et al. Journal of magnetic resonance imaging : JMRI 2022 - Radiomic-Based MRI for Classification of Solitary Brain Metastases Subtypes From Primary Lymphoma of the Central Nervous System.
Zhao Lin-Mei et al. Journal of magnetic resonance imaging : JMRI 2022 - Importance of Echocardiography and Clinical "Red Flags" in Guiding Genetic Screening for Fabry Disease.
Citro Rodolfo et al. Frontiers in cardiovascular medicine 2022 9838200 - Association of Lipoprotein (a) in Coronary Artery Disease in Young Individuals.
Patted Aishwarya et al. The Journal of the Association of Physicians of India 2022 70(4) 11-12 - Artificial Intelligence-Enabled Electrocardiography Predicts Left Ventricular Dysfunction and Future Cardiovascular Outcomes: A Retrospective Analysis.
Chen Hung-Yi et al. Journal of personalized medicine 2022 12(3) - Investigation of the Familial Risk of Rheumatic Heart Disease with Systematic Echocardiographic Screening: Data from the PROVAR+ Family Study.
Franco Juliane et al. Pathogens (Basel, Switzerland) 2022 11(2) - Artificial Intelligence-Enabled Electrocardiogram Estimates Left Atrium Enlargement as a Predictor of Future Cardiovascular Disease.
Lou Yu-Sheng et al. Journal of personalized medicine 2022 12(2) - Automated Detection of Candidate Subjects With Cerebral Microbleeds Using Machine Learning.
Sundaresan Vaanathi et al. Frontiers in neuroinformatics 2022 15777828
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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.
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- Page last updated:Apr 25, 2024
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