Pneumothorax
What's New
Last Posted: Mar 07, 2023
- Hospital-wide survey of clinical experience with artificial intelligence applied to daily chest radiographs.
Hyun Joo Shin et al. PloS one 2023 18(3) e0282123 - Chest X-ray in Emergency Radiology: What Artificial Intelligence Applications Are Available?
Giovanni Irmici et al. Diagnostics (Basel, Switzerland) 2023 13(2) - Diagnostic accuracy of a commercially available deep learning algorithm in supine chest radiographs following trauma.
Gipson Jacob et al. The British journal of radiology 2022 20210979 - Diagnostic effect of artificial intelligence solution for referable thoracic abnormalities on chest radiography: a multicenter respiratory outpatient diagnostic cohort study.
Jin Kwang Nam et al. European radiology 2022 - Prediction of locations in medical images using orthogonal neural networks.
Kim Jong Soo et al. European journal of radiology open 2021 8100388 - Deep learning applied to automatic disease detection using chest X-rays.
Moses Daniel A et al. Journal of medical imaging and radiation oncology 2021 - Colorectal cancer risk in families with Birt-Hogg-Dubé syndrome increased.
Sattler Elke C et al. European journal of cancer (Oxford, England : 1990) 2021 151168-174 - Performance of a deep-learning algorithm for referable thoracic abnormalities on chest radiographs: A multicenter study of a health screening cohort.
Kim Eun Young et al. PloS one 2021 16(2) e0246472 - 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 - Machine learning can predict disease manifestations and outcomes in lymphangioleiomyomatosis.
Chernbumroong Saisakul et al. The European respiratory journal 2020 Dec - CheXLocNet: Automatic localization of pneumothorax in chest radiographs using deep convolutional neural networks.
Wang Hongyu et al. PloS one 2020 15(11) e0242013 - A multi-institutional experience in vascular Ehlers-Danlos syndrome diagnosis.
Shalhub Sherene et al. Journal of vascular surgery 2020 71(1) 149-157 - CT Fluoroscopy Guided Thoracic Biopsies (CTTB) Are Highly Accurate and Safe: Outcomes and Predictive Modeling of Complications Utilizing Machine Learning.
Mortani Barbosa Eduardo J et al. Academic radiology 2020 May - Deep learning algorithm for surveillance of pneumothorax after lung biopsy: a multicenter diagnostic cohort study.
Hwang Eui Jin et al. European radiology 2020 Mar - Chest Radiograph Interpretation with Deep Learning Models: Assessment with Radiologist-adjudicated Reference Standards and Population-adjusted Evaluation.
Majkowska Anna et al. Radiology 2019 Dec 191293 - Crowdsourcing pneumothorax annotations using machine learning annotations on the NIH chest X-ray dataset.
Filice Ross W et al. Journal of digital imaging 2019 Nov - The Relevance of Family History Taking in the Detection and Management of Birt-Hogg-Dubé Syndrome.
Torricelli Elena et al. Respiration; international review of thoracic diseases 2019 Jul 1-8 - Role of Radiologists in the Diagnosis of Unsuspected Birt-Hogg-Dubé Syndrome in a Tertiary Clinical Practice.
Lee Elizabeth et al. AJR. American journal of roentgenology 2019 May 1-6 - CLINGEN Actionability Report for Loeys-Dietz Syndrome - SMAD3, TGFB2, TGFB3, TGFBR1, TGFBR2
ClinGen Actionability Working Group - CLINGEN Actionability Report for Birt-Hogg-Dub� syndrome - FLCN
ClinGen Actionability Working Group - CLINGEN Actionability Report for Familial papillary renal cell carcinoma 1 - MET
ClinGen Actionability Working Group - CLINGEN Actionability Report for Marfan Syndrome - FBN1
ClinGen Actionability Working Group - CLINGEN Actionability Report for Tuberous Sclerosis Complex (TSC)-TSC1, TSC2
ClinGen Actionability Working Group - A rapid NGS strategy for comprehensive molecular diagnosis of Birt-Hogg-Dubé syndrome in patients with primary spontaneous pneumothorax.
Zhang Xinxin et al. Respiratory research 2016 May 17(1) 64 - Molecular adequacy of image-guided rebiopsies for molecular retesting in advanced non-small cell lung cancer: a single centre experience.
Tokaca Nadza et al. Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer 2017 Oct - Implementing precision cancer medicine in the public health services of Norway: the diagnostic infrastructure and a cost estimate.
Ree Anne Hansen et al. ESMO open 2017 2(2) e000158 - Implementation of a Multicenter Biobanking Collaboration for Next-Generation Sequencing-Based Biomarker Discovery Based on Fresh Frozen Pretreatment Tumor Tissue Biopsies.
Bins Sander et al. The oncologist 2016 Sep - The effects of prenatal genetic analysis on fetuses born to carrier mothers with primary immunodeficiency diseases.
Lee Wen-I et al. Annals of medicine 2016 Feb 1-8 - Bronchoscopy
From NHLBI health topic site - LAM
From NHLBI health topic site
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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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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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