Methods for clinical evaluation of artificial intelligence algorithms for medical diagnosis
Adequate clinical evaluation of artificial intelligence (AI) algorithms before adoption in
practice is critical. Clinical evaluation aims to confirm acceptable AI performance through …
practice is critical. Clinical evaluation aims to confirm acceptable AI performance through …
Deep machine learning for medical diagnosis, application to lung cancer detection: a review
HT Gayap, MA Akhloufi - BioMedInformatics, 2024 - mdpi.com
Deep learning has emerged as a powerful tool for medical image analysis and diagnosis,
demonstrating high performance on tasks such as cancer detection. This literature review …
demonstrating high performance on tasks such as cancer detection. This literature review …
Multicentre external validation of a commercial artificial intelligence software to analyse chest radiographs in health screening environments with low disease …
Objectives To externally validate the performance of a commercial AI software program for
interpreting CXRs in a large, consecutive, real-world cohort from primary healthcare centres …
interpreting CXRs in a large, consecutive, real-world cohort from primary healthcare centres …
[HTML][HTML] Randomized clinical trials of artificial intelligence in medicine: why, when, and how?
1Department of Radiology and Research Institute of Radiology, Asan Medical Center,
University of Ulsan College of Medicine, Seoul, Korea; 2Department of Radiology, Seoul St …
University of Ulsan College of Medicine, Seoul, Korea; 2Department of Radiology, Seoul St …
[HTML][HTML] Conventional versus artificial intelligence-assisted interpretation of chest radiographs in patients with acute respiratory symptoms in emergency department: a …
Objective It is unknown whether artificial intelligence-based computer-aided detection (AI-
CAD) can enhance the accuracy of chest radiograph (CR) interpretation in real-world clinical …
CAD) can enhance the accuracy of chest radiograph (CR) interpretation in real-world clinical …
2023 survey on user experience of artificial intelligence software in radiology by the Korean Society of Radiology
Objective In Korea, radiology has been positioned towards the early adoption of artificial
intelligence-based software as medical devices (AI-SaMDs); however, little is known about …
intelligence-based software as medical devices (AI-SaMDs); however, little is known about …
Deep learning for estimating lung capacity on chest radiographs predicts survival in idiopathic pulmonary fibrosis
Background Total lung capacity (TLC) has been estimated with use of chest radiographs
based on time-consuming methods, such as planimetric techniques and manual …
based on time-consuming methods, such as planimetric techniques and manual …
Conceptual review of outcome metrics and measures used in clinical evaluation of artificial intelligence in radiology
Artificial intelligence (AI) has numerous applications in radiology. Clinical research studies
to evaluate the AI models are also diverse. Consequently, diverse outcome metrics and …
to evaluate the AI models are also diverse. Consequently, diverse outcome metrics and …
A deep learning-based model improves diagnosis of early gastric cancer under narrow band imaging endoscopy
D Tang, M Ni, C Zheng, X Ding, N Zhang, T Yang… - Surgical …, 2022 - Springer
Background Diagnosis of early gastric cancer (EGC) under narrow band imaging endoscopy
(NBI) is dependent on expertise and skills. We aimed to elucidate whether artificial …
(NBI) is dependent on expertise and skills. We aimed to elucidate whether artificial …
Artificial intelligence system for identification of false-negative interpretations in chest radiographs
Objectives To investigate the efficacy of an artificial intelligence (AI) system for the
identification of false negatives in chest radiographs that were interpreted as normal by …
identification of false negatives in chest radiographs that were interpreted as normal by …