Assessment of the effect of a comprehensive chest radiograph deep learning model on radiologist reports and patient outcomes: a real-world observational study

Deep learning, computer-aided radiography reading for tuberculosis: a diagnostic accuracy study from a tertiary hospital in India

(2020) Madlen Nash et al.   Scientific Reports

Deep learning algorithm for surveillance of pneumothorax after lung biopsy: a multicenter diagnostic cohort study

(2020) Eui Jin Hwang et al.   EUROPEAN RADIOLOGY

Deep Learning Localization of Pneumonia

(2020) Brian Hurt et al.   JOURNAL OF THORACIC IMAGING

Potential of deep learning in assessing pneumoconiosis depicted on digital chest radiography

(2020) Xiaohua Wang et al.   OCCUPATIONAL AND ENVIRONMENTAL MEDICINE

Impact of Confounding Thoracic Tubes and Pleural Dehiscence Extent on Artificial Intelligence Pneumothorax Detection in Chest Radiographs

(2020) Johannes Rueckel et al.   INVESTIGATIVE RADIOLOGY

A promising approach for screening pulmonary hypertension based on frontal chest radiographs using deep learning: A retrospective study

(2020) Xiao-Ling Zou et al.   PLoS One

Deep Learning–based Automatic Detection Algorithm for Reducing Overlooked Lung Cancers on Chest Radiographs

(2020) Sowon Jang et al.   RADIOLOGY

Array programming with NumPy

(2020) Charles R. Harris et al.   NATURE

Deep Learning Algorithms with Demographic Information Help to Detect Tuberculosis in Chest Radiographs in Annual Workers’ Health Examination Data

(2019) Seok-Jae Heo et al.   International Journal of Environmental Research and Public Health

Application of deep learning–based computer-aided detection system: detecting pneumothorax on chest radiograph after biopsy

(2019) Sohee Park et al.   EUROPEAN RADIOLOGY

Impact of the rise of artificial intelligence in radiology: What do radiologists think?

(2019) Q. Waymel et al.   Diagnostic and Interventional Imaging

Efficient Deep Network Architectures for Fast Chest X-Ray Tuberculosis Screening and Visualization

(2019) F. Pasa et al.   Scientific Reports

Identifying pulmonary nodules or masses on chest radiography using deep learning: external validation and strategies to improve clinical practice

(2019) C.-H. Liang et al.   CLINICAL RADIOLOGY

Using artificial intelligence to read chest radiographs for tuberculosis detection: A multi-site evaluation of the diagnostic accuracy of three deep learning systems

(2019) Zhi Zhen Qin et al.   Scientific Reports

Deep Convolutional Neural Network–based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs

(2019) Yongsik Sim et al.   RADIOLOGY

Deep Learning for Chest Radiograph Diagnosis in the Emergency Department

(2019) Eui Jin Hwang et al.   RADIOLOGY

The past, present and future role of artificial intelligence in imaging

(2018) Mohammad Ihsan Fazal et al.   EUROPEAN JOURNAL OF RADIOLOGY

The Role of Artificial Intelligence in Diagnostic Radiology: A Survey at a Single Radiology Residency Training Program

(2018) Fernando Collado-Mesa et al.   Journal of the American College of Radiology

Deep learning in chest radiography: Detection of findings and presence of change

(2018) Ramandeep Singh et al.   PLoS One

Machine Learning for Medical Imaging

(2017) Bradley J. Erickson et al.   RADIOGRAPHICS

Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural Networks

(2017) Paras Lakhani et al.   RADIOLOGY

Missed lung cancer: when, where, and why?

(2017) Annemilia del Ciello et al.   Diagnostic and Interventional Radiology

Causes of death among cancer patients

(2016) NG Zaorsky et al.   ANNALS OF ONCOLOGY

Radiomics: Images Are More than Pictures, They Are Data

(2016) Robert J. Gillies et al.   RADIOLOGY

Machine learning: Trends, perspectives, and prospects

(2015) M. I. Jordan et al.   SCIENCE

Cognitive and System Factors Contributing to Diagnostic Errors in Radiology

(2013) Cindy S. Lee et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

Digital chest radiography: an update on modern technology, dose containment and control of image quality

(2008) Cornelia Schaefer-Prokop et al.   EUROPEAN RADIOLOGY