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Public Health Genomics and Precision Health Knowledge Base (v9.0)
PHGKB
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Public Health Genomics Branch
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Precision Health Database|Search|Public Health Genomics and Precision Health Knowledge Base (PHGKB)
Heart, Lung, Blood and Sleep Disorders
Last data update: May 03, 2024
. (Total: 63769 Documents since 2012)
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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
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Chest X-ray in Emergency Radiology: What Artificial Intelligence Applications Are Available?
Giovanni Irmici et al. Diagnostics (Basel, Switzerland) 2023 13(2)
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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
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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
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Prediction of locations in medical images using orthogonal neural networks.
Kim Jong Soo et al. European journal of radiology open 2021 8100388
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Deep learning applied to automatic disease detection using chest X-rays.
Moses Daniel A et al. Journal of medical imaging and radiation oncology 2021
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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
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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
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Machine learning can predict disease manifestations and outcomes in lymphangioleiomyomatosis.
Chernbumroong Saisakul et al. The European respiratory journal 2020 Dec
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CheXLocNet: Automatic localization of pneumothorax in chest radiographs using deep convolutional neural networks.
Wang Hongyu et al. PloS one 2020 15(11) e0242013
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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
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Deep learning algorithm for surveillance of pneumothorax after lung biopsy: a multicenter diagnostic cohort study.
Hwang Eui Jin et al. European radiology 2020 Mar
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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
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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
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Page last reviewed:
Feb 1, 2024
Page last updated:
May 03, 2024
Content source:
Public Health Genomics Branch in the Division of Blood Disorders and Public Health Genomics
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National Center on Birth Defects and Developmental Disabilities
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