AIMC Topic: Radiologists

Clear Filters Showing 431 to 440 of 503 articles

Assessing the Performance of Artificial Intelligence Assistance for Prostate MRI: A Two-Center Study Involving Radiologists With Different Experience Levels.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Artificial intelligence (AI) assistance may enhance radiologists' performance in detecting clinically significant prostate cancer (csPCa) on MRI. Further validation is needed for radiologists with different experiences.

Breast Cancer Detection with Standalone AI versus Radiologist Interpretation of Unilateral Surveillance Mammography after Mastectomy.

Radiology
Background Limited data are available regarding the accuracy of artificial intelligence (AI) algorithms trained on bilateral mammograms for second breast cancer surveillance in patients with a personal history of breast cancer treated with unilateral...

Human-AI Interaction in the ScreenTrustCAD Trial: Recall Proportion and Positive Predictive Value Related to Screening Mammograms Flagged by AI CAD versus a Human Reader.

Radiology
Background The ScreenTrustCAD trial was a prospective study that evaluated the cancer detection rates for combinations of artificial intelligence (AI) computer-aided detection (CAD) and two radiologists. The results raised concerns about the tendency...

[Evaluating the accuracy of large language models in answering mammography screening questions in Italian and English: a study based on the Eusobi guidelines.].

Recenti progressi in medicina
INTRODUCTION: Artificial intelligence (AI) is transforming various aspects of everyday life, including healthcare, through large language models (LLMs) like ChatGPT, Gemini, and Copilot. These systems are increasingly used to disseminate medical info...

The influence of a deep learning tool on the performance of oral and maxillofacial radiologists in the detection of apical radiolucencies.

Dento maxillo facial radiology
OBJECTIVES: This study aimed to assess the impact of a deep learning model on oral radiologists' ability to detect periapical radiolucencies on periapical radiographs. The secondary objective was to conduct a regression analysis to evaluate the effec...

Comparative analysis of diagnostic performance in mammography: A reader study on the impact of AI assistance.

PloS one
PURPOSE: This study evaluates the impact of artificial intelligence (AI) assistance on the diagnostic performance of radiologists with varying levels of experience in interpreting mammograms in a Malaysian tertiary referral center, particularly in wo...

Large language models as an academic resource for radiologists stepping into artificial intelligence research.

Current problems in diagnostic radiology
BACKGROUND: Radiologists increasingly use artificial intelligence (AI) to enhance diagnostic accuracy and optimize workflows. However, many lack the technical skills to effectively apply machine learning (ML) and deep learning (DL) algorithms, limiti...

Familiarity, confidence and preference of artificial intelligence feedback and prompts by Australian breast cancer screening readers.

Australian health review : a publication of the Australian Hospital Association
Objectives This study explored the familiarity, perceptions and confidence of Australian radiology clinicians involved in reading screening mammograms, regarding artificial intelligence (AI) applications in breast cancer detection. Methods Sixty-five...