Artificial intelligence system for identification of false-negative interpretations in chest radiographs
暂无分享,去创建一个
J. Nam | E. J. Hwang | J. Goo | C. Park | Hyungjin Kim | Chang Hyun Lee | Hyewon Choi | S. Yoon | Hyun-Ju Lee | Jongsoo Park | Wonju Hong | Hyun-Ju Lee | C. Lee
[1] Eui Jin Hwang,et al. Deep Learning for Detection of Pulmonary Metastasis on Chest Radiographs. , 2021, Radiology.
[2] Sang Min Lee,et al. Added Value of Deep Learning-based Detection System for Multiple Major Findings on Chest Radiographs: A Randomized Crossover Study. , 2021, Radiology.
[3] Eui Jin Hwang,et al. Undetected Lung Cancer at Posteroanterior Chest Radiography: Potential Role of a Deep Learning-based Detection Algorithm. , 2020, Radiology. Cardiothoracic imaging.
[4] Eui Jin Hwang,et al. Development and validation of a deep learning algorithm detecting 10 common abnormalities on chest radiographs , 2020, European Respiratory Journal.
[5] Sung Soo Lee,et al. Deep Learning-based Automatic Detection Algorithm for Reducing Overlooked Lung Cancers on Chest Radiographs. , 2020, Radiology.
[6] E. J. Hwang,et al. Automated identification of chest radiographs with referable abnormality with deep learning: need for recalibration , 2020, European Radiology.
[7] Bram van Ginneken,et al. COVID-19 on Chest Radiographs: A Multireader Evaluation of an Artificial Intelligence System , 2020, Radiology.
[8] Constantine A Raptis,et al. ACR Appropriateness Criteria® Hemoptysis. , 2020, Journal of the American College of Radiology : JACR.
[9] Eui Jin Hwang,et al. Clinical Implementation of Deep Learning in Thoracic Radiology: Potential Applications and Challenges , 2020, Korean journal of radiology.
[10] J. Ioannidis,et al. Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies , 2020, BMJ.
[11] Eui Jin Hwang,et al. Deep learning algorithm for surveillance of pneumothorax after lung biopsy: a multicenter diagnostic cohort study , 2020, European Radiology.
[12] E. Kotter,et al. Deep Convolutional Neural Network-based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs. , 2019, Radiology.
[13] Jin Mo Goo,et al. Deep Learning for Chest Radiograph Diagnosis in the Emergency Department. , 2019, Radiology.
[14] Peter Hardy,et al. Perceptual and Interpretive Error in Diagnostic Radiology-Causes and Potential Solutions. , 2019, Academic radiology.
[15] Eui Jin Hwang,et al. Development and Validation of a Deep Learning–Based Automated Detection Algorithm for Major Thoracic Diseases on Chest Radiographs , 2019, JAMA network open.
[16] Eui Jin Hwang,et al. Development and Validation of Deep Learning-based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs. , 2019, Radiology.
[17] Jonathan H. Chung,et al. ACR Appropriateness Criteria® Acute Respiratory Illness in Immunocompromised Patients. , 2012, Journal of the American College of Radiology : JACR.
[18] Ben Van Calster,et al. Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators. , 2018, European urology.
[19] Eui Jin Hwang,et al. Development and Validation of a Deep Learning–based Automatic Detection Algorithm for Active Pulmonary Tuberculosis on Chest Radiographs , 2018, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.
[20] Jonathan H. Chung,et al. ACR Appropriateness Criteria® Chronic Dyspnea-Noncardiovascular Origin. , 2018, Journal of the American College of Radiology : JACR.
[21] Jonathan H. Chung,et al. ACR Appropriateness Criteria® Acute Respiratory Illness in Immunocompetent Patients. , 2018, Journal of the American College of Radiology : JACR.
[22] Sohil H. Patel,et al. Fundamentals of Diagnostic Error in Imaging. , 2018, Radiographics : a review publication of the Radiological Society of North America, Inc.
[23] Jonathan H. Chung,et al. ACR Appropriateness Criteria® Imaging of Possible Tuberculosis. , 2017, Journal of the American College of Radiology : JACR.
[24] Brian Gale,et al. Interpretive Error in Radiology. , 2017, AJR. American journal of roentgenology.
[25] Michael A. Bruno,et al. Understanding and Confronting Our Mistakes: The Epidemiology of Error in Radiology and Strategies for Error Reduction. , 2015, Radiographics : a review publication of the Radiological Society of North America, Inc.
[26] N. Miyashita,et al. Detection failure rate of chest radiography for the identification of nursing and healthcare-associated pneumonia. , 2015, Journal of infection and chemotherapy : official journal of the Japan Society of Chemotherapy.
[27] Benjamin R Saville,et al. Decision curve analysis. , 2015, JAMA.
[28] L. Berlin. Radiologic errors, past, present and future , 2014, Diagnosis.
[29] Jennifer J Donald,et al. Common patterns in 558 diagnostic radiology errors , 2012, Journal of medical imaging and radiation oncology.