The current and future state of AI interpretation of medical images
The Current and Future State of AI Interpretation of Medical Images | New England Journal of
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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 …
Commercially available chest radiograph AI tools for detecting airspace disease, pneumothorax, and pleural effusion
L Lind Plesner, FC Müller, MW Brejnebøl, LC Laustrup… - Radiology, 2023 - pubs.rsna.org
Background Commercially available artificial intelligence (AI) tools can assist radiologists in
interpreting chest radiographs, but their real-life diagnostic accuracy remains unclear …
interpreting chest radiographs, but their real-life diagnostic accuracy remains unclear …
Artificial intelligence in commercial fracture detection products: a systematic review and meta-analysis of diagnostic test accuracy
J Husarek, S Hess, S Razaeian, TD Ruder… - Scientific Reports, 2024 - nature.com
Conventional radiography (CR) is primarily utilized for fracture diagnosis. Artificial
intelligence (AI) for CR is a rapidly growing field aimed at enhancing efficiency and …
intelligence (AI) for CR is a rapidly growing field aimed at enhancing efficiency and …
Examination-Level Supervision for Deep Learning–based Intracranial Hemorrhage Detection on Head CT Scans
Purpose To compare the effectiveness of weak supervision (ie, with examination-level labels
only) and strong supervision (ie, with image-level labels) in training deep learning models …
only) and strong supervision (ie, with image-level labels) in training deep learning models …
Impact of human and artificial intelligence collaboration on workload reduction in medical image interpretation
M Chen, Y Wang, Q Wang, J Shi, H Wang, Z Ye… - NPJ Digital …, 2024 - nature.com
Clinicians face increasing workloads in medical imaging interpretation, and artificial
intelligence (AI) offers potential relief. This meta-analysis evaluates the impact of human-AI …
intelligence (AI) offers potential relief. This meta-analysis evaluates the impact of human-AI …
A survey of ASER members on artificial intelligence in emergency radiology: trends, perceptions, and expectations
Purpose There is a growing body of diagnostic performance studies for emergency
radiology-related artificial intelligence/machine learning (AI/ML) tools; however, little is …
radiology-related artificial intelligence/machine learning (AI/ML) tools; however, little is …
Artificial intelligence CAD tools in trauma imaging: a sco** review from the American Society of Emergency Radiology (ASER) AI/ML Expert Panel
Abstract Background AI/ML CAD tools can potentially improve outcomes in the high-stakes,
high-volume model of trauma radiology. No prior sco** review has been undertaken to …
high-volume model of trauma radiology. No prior sco** review has been undertaken to …
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 …
Assessing the performance of models from the 2022 RSNA Cervical Spine Fracture Detection Competition at a level I trauma center
Purpose To evaluate the performance of the top models from the RSNA 2022 Cervical Spine
Fracture Detection challenge on a clinical test dataset of both noncontrast and contrast …
Fracture Detection challenge on a clinical test dataset of both noncontrast and contrast …