The current and future state of AI interpretation of medical images

P Rajpurkar, MP Lungren - New England Journal of Medicine, 2023 - Mass Medical Soc
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

SH Park, K Han, HY Jang, JE Park, JG Lee, DW Kim… - Radiology, 2023 - pubs.rsna.org
Adequate clinical evaluation of artificial intelligence (AI) algorithms before adoption in
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 …

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 …

Examination-Level Supervision for Deep Learning–based Intracranial Hemorrhage Detection on Head CT Scans

J Teneggi, PH Yi, J Sulam - Radiology: Artificial Intelligence, 2023 - pubs.rsna.org
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 …

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 …

A survey of ASER members on artificial intelligence in emergency radiology: trends, perceptions, and expectations

A Agrawal, GD Khatri, B Khurana, AD Sodickson… - Emergency …, 2023 - Springer
Purpose There is a growing body of diagnostic performance studies for emergency
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

D Dreizin, PV Staziaki, GD Khatri, NM Beckmann… - Emergency …, 2023 - Springer
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 …

Multicentre external validation of a commercial artificial intelligence software to analyse chest radiographs in health screening environments with low disease …

C Kim, Z Yang, SH Park, SH Hwang, YW Oh… - European …, 2023 - Springer
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 …

Assessing the performance of models from the 2022 RSNA Cervical Spine Fracture Detection Competition at a level I trauma center

Z Hu, M Patel, RL Ball, HM Lin… - Radiology: Artificial …, 2024 - pubs.rsna.org
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 …