AI Improves Nodule Detection on Chest Radiographs in a Health Screening Population: A Randomized Controlled Trial

Accuracy of Automated Computer-Aided Diagnosis for Stroke Imaging: A Critical Evaluation of Current Evidence

(2022) Joanna M. Wardlaw et al.   STROKE

Deep Learning Prediction of Survival in Patients with Chronic Obstructive Pulmonary Disease Using Chest Radiographs

(2022) Ju Gang Nam et al.   RADIOLOGY

Performance of a deep-learning algorithm for referable thoracic abnormalities on chest radiographs: A multicenter study of a health screening cohort

(2021) Eun Young Kim et al.   PLoS One

AI-based improvement in lung cancer detection on chest radiographs: results of a multi-reader study in NLST dataset

(2021) Hyunsuk Yoo et al.   EUROPEAN RADIOLOGY

Value of a deep learning-based algorithm for detecting Lung-RADS category 4 nodules on chest radiographs in a health checkup population: estimation of the sample size for a randomized controlled trial

(2021) Ju Gang Nam et al.   EUROPEAN RADIOLOGY

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

(2020) Sowon Jang et al.   RADIOLOGY

Performance of a Deep Learning Algorithm Compared with Radiologic Interpretation for Lung Cancer Detection on Chest Radiographs in a Health Screening Population

(2020) Jong Hyuk Lee et al.   RADIOLOGY

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI Extension

(2020) Xiaoxuan Liu et al.   BMJ-British Medical Journal

External Evaluation of 3 Commercial Artificial Intelligence Algorithms for Independent Assessment of Screening Mammograms

(2020) Mattie Salim et al.   JAMA Oncology

Development and validation of a deep learning algorithm detecting 10 common abnormalities on chest radiographs

(2020) Ju Gang Nam et al.   EUROPEAN RESPIRATORY JOURNAL

Feasibility of lung cancer screening in developing countries: challenges, opportunities and way forward

(2019) Abhishek Shankar et al.   Translational Lung Cancer Research

Evaluating Health Technology Through Pragmatic Trials

(2018) Eric D. Peterson et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Development and Validation of Deep Learning–based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs

(2018) Ju Gang Nam et al.   RADIOLOGY

Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists

(2018) Pranav Rajpurkar et al.   PLOS MEDICINE

Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017

(2017) Heber MacMahon et al.   RADIOLOGY

The PRECIS-2 tool: designing trials that are fit for purpose

(2015) K. Loudon et al.   BMJ-British Medical Journal

The PRECIS-2 tool: designing trials that are fit for purpose

(2015) K. Loudon et al.   BMJ-British Medical Journal

Evaluation of Individuals With Pulmonary Nodules: When Is It Lung Cancer?

(2013) Michael K. Gould et al.   CHEST

Results of the Two Incidence Screenings in the National Lung Screening Trial

(2013) Denise R. Aberle et al.   NEW ENGLAND JOURNAL OF MEDICINE

Lung Cancer Screening with Computer Aided Detection Chest Radiography: Design and Results of a Randomized, Controlled Trial

(2013) Peter J. Mazzone et al.   PLoS One

A population-based cohort study of chest x-ray screening in smokers: lung cancer detection findings and follow-up

(2012) Lorenzo Dominioni et al.   BMC CANCER

Screening by Chest Radiograph and Lung Cancer Mortality

(2011) Martin M. Oken et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION