Deep Learning for Triage of Chest Radiographs 546 radiology. rsna. org n Radiology:
Volume 290: Number 2—February 2019 reasonably well (AUC= 0.93), but its performance …

Chest radiographs are often obtained as a screening for early diagnosis tool to rule out
abnormalities mainly related to different cardiovascular and respiratory diseases. Reading …

Background: Chest X-rays are the most commonly performed, cost-effective diagnostic
imaging tests ordered by physicians. A clinically validated AI system that can reliably …

Dr Goo is a professor in the Department of Radiology at Seoul National University College of
Medicine. His research interests are imaging of lung cancer, lung cancer screening, and the …

SirdWe read with interest the recent article entitled “Validation study of machine-learning
chest radiograph software in primary and secondary medicine”. 1 Imaging triage is an …

Objectives To evaluate whether deep learning–based detection algorithms (DLD)–based
triaging can reduce outpatient chest radiograph interpretation workload while maintaining …

© Quantitative Imaging in Medicine and Surgery. All rights reserved. Quant Imaging Med
Surg 2021; 11 (5): 2204-2207| http://dx. doi. org/10.21037/qims-20-1306 that there is great …

Importance The efficient and accurate interpretation of radiologic images is paramount.
Objective To evaluate whether a deep learning–based artificial intelligence (AI) engine used …

Objectives To evaluate the calibration of a deep learning (DL) model in a diagnostic cohort
and to improve model's calibration through recalibration procedures. Methods Chest …

Background Deep learning has the potential to augment the use of chest radiography in
clinical radiology, but challenges include poor generalizability, spectrum bias, and difficulty …