Last Posted: Mar 03, 2023
- Diagnosis of malignant pleural effusion with combinations of multiple tumor markers: A comparison study of five machine learning models.
Yixi Zhang et al. The International journal of biological markers 2023 3936155231158125
- Chest X-ray in Emergency Radiology: What Artificial Intelligence Applications Are Available?
Giovanni Irmici et al. Diagnostics (Basel, Switzerland) 2023 13(2)
- Differentiation of malignant from benign pleural effusions based on artificial intelligence.
Wang Sufei et al. Thorax 2022
- Diagnostic accuracy of a commercially-available, deep learning-based chest-Xray interpretation software for detecting culture-confirmed pulmonary tuberculosis.
Tavaziva Gamuchirai et al. International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases 2022
- Tracking and predicting COVID-19 radiological trajectory on chest X-rays using deep learning.
Gourdeau Daniel et al. Scientific reports 2022 12(1) 5616
- Value of metagenomic next-generation sequencing in children with severe infectious diseases.
Zheng Yi-Hui et al. Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics 2022 24(3) 273-278
- [A preliminary investigation on a deep learning convolutional neural networks based pulmonary tuberculosis CT diagnostic model].
Wu S C et al. Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases 2021 44(5) 450-455
- Diagnostic accuracy of adenosine deaminase for pleural tuberculosis in a low prevalence setting: A machine learning approach within a 7-year prospective multi-center study.
Garcia-Zamalloa Alberto et al. PloS one 2021 16(11) e0259203
- Genetic Profiling of Cell-Free DNA From Pleural Effusion in Advanced Lung Cancer as a Surrogate for Tumor Tissue and Revealed Additional Clinical Actionable Targets.
Tu Hai-Yan et al. Clinical lung cancer 2021
- Recalibration of deep learning models for abnormality detection in smartphone-captured chest radiograph.
Kuo Po-Chih et al. NPJ digital medicine 2021 Feb 4(1) 25
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.
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