Reducing Errors Resulting From Commonly Missed Chest Radiography Findings

Chest - Tập 163 - Trang 634-649 - 2023
Warren B. Gefter1, Hiroto Hatabu2
1Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, PA
2Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA

Tài liệu tham khảo

Gefter, 2023, Commonly missed findings on chest radiographs: causes and consequences, Chest, 163, 650, 10.1016/j.chest.2022.10.039

Delrue, 2011, Difficulties in the interpretation of chest radiography, 27

McAdams, 2006, Recent advances in chest radiography, Radiology, 241, 663, 10.1148/radiol.2413051535

Silosky, 2022, Features to consider when selecting displays for remote reading, J Am Coll Radiol, 73, 10.1016/j.jacr.2021.09.038

Bevins

Drew, 2013, The invisible gorilla strikes again: sustained inattentional blindness in expert observers, Phychol Sci, 24(9), 1848, 10.1177/0956797613479386

Itri, 2018, Fundamentals of diagnostic error in imaging, Radiographics, 38(6), 1845, 10.1148/rg.2018180021

Bruno, 2015, Understanding and confronting our mistakes: the epidemiology of error in radiology and strategies for error reduction, Radiographics, 35(6), 1668, 10.1148/rg.2015150023

Calli, 2021, Deep learning for chest X-ray analysis: a survey, Medical Image Analysis, 72, 10.1016/j.media.2021.102125

Dunnmon, 2019, Assessment of convolutional neural networks for automated classification of chest radiographs, Radiology, 290(2), 537, 10.1148/radiol.2018181422

Majkowska, 2020, Chest radiograph interpretation with deep learning models: assessment with radiologist-adjudicated reference standards and population-adjusted evaluation, Radiology, 294, 421, 10.1148/radiol.2019191293

Nam, 2019, Development and validation of deep learning-based automatic detection algorithm for malignant pulmonary nodules on chest radiographs, Radiology, 290(1), 218, 10.1148/radiol.2018180237

Yoo, 2019, Validation of a deep learning algorithm for the detection of malignant pulmonary nodules in chest radiographs, JAMA Netw Open, 3, e2017135, 10.1001/jamanetworkopen.2020.17135

Felson, 1973, 105

Gawande, 2010

Berbaum, 2006, Can a checklist reduce SOS errors in chest radiography?, Acad Radiol, 13(3), 296, 10.1016/j.acra.2005.11.032

Kok, 2017, Does the use of a checklist help medical students in the detection of abnormalities on a chest radiograph, J Digit Imaging, 30(6), 726, 10.1007/s10278-017-9979-0

Chacko, 2022