AI Medical Compendium Journal:
Radiology

Showing 1 to 10 of 374 articles

Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis.

Radiology
Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to critically evaluate the performance of AI before it can become a modality used for independe...

Opportunistic Screening: Scientific Expert Panel.

Radiology
Radiologic tests often contain rich imaging data not relevant to the clinical indication. Opportunistic screening refers to the practice of systematically leveraging these incidental imaging findings. Although opportunistic screening can apply to ima...

Performance of ChatGPT on a Radiology Board-style Examination: Insights into Current Strengths and Limitations.

Radiology
Background ChatGPT is a powerful artificial intelligence large language model with great potential as a tool in medical practice and education, but its performance in radiology remains unclear. Purpose To assess the performance of ChatGPT on radiolog...

Automation Bias in Mammography: The Impact of Artificial Intelligence BI-RADS Suggestions on Reader Performance.

Radiology
Background Automation bias (the propensity for humans to favor suggestions from automated decision-making systems) is a known source of error in human-machine interactions, but its implications regarding artificial intelligence (AI)-aided mammography...

Interstitial Lung Abnormalities at CT in the Korean National Lung Cancer Screening Program: Prevalence and Deep Learning-based Texture Analysis.

Radiology
Background Interstitial lung abnormalities (ILAs) are associated with worse clinical outcomes, but ILA with lung cancer screening CT has not been quantitatively assessed. Purpose To determine the prevalence of ILA at CT examinations from the Korean N...

Interactive Explainable Deep Learning Model Informs Prostate Cancer Diagnosis at MRI.

Radiology
Background Clinically significant prostate cancer (PCa) diagnosis at MRI requires accurate and efficient radiologic interpretation. Although artificial intelligence may assist in this task, lack of transparency has limited clinical translation. Purpo...