Diagnostic and interventional radiology (Ankara, Turkey)
39248152
PURPOSE: This study aimed to evaluate the performance of large language models (LLMs) and multimodal LLMs in interpreting the Breast Imaging Reporting and Data System (BI-RADS) categories and providing clinical management recommendations for breast r...
Structured reporting (SR) has long been a goal in radiology to standardize and improve the quality of radiology reports. Despite evidence that SR reduces errors, enhances comprehensiveness, and increases adherence to guidelines, its widespread adopti...
BACKGROUND: The impression section integrates key findings of a radiology report but can be subjective and variable. We sought to fine-tune and evaluate an open-source Large Language Model (LLM) in automatically generating impressions from the remain...
Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
39315514
To evaluate the clinical performance of a Protocol Recommendation System (PRS) automatic protocolling of chest CT imaging requests. 322 387 consecutive historical imaging requests for chest CT between 2017 and 2022 were extracted from a radiology i...
PURPOSE: Retrospectively compare image quality, radiologist diagnostic confidence, and time for images to reach PACS for contrast enhanced abdominopelvic CT examinations created on the scanner console by technologists versus those generated automatic...
OBJECTIVE: The ACR Thyroid Imaging, Reporting, and Data System (TI-RADS) uses a score based on ultrasound (US) imaging to stratify the risk of nodule malignancy and recommend appropriate follow-up. This study aims to analyze US reports and explore ho...
Large language models like ChatGPT, with their growing accessibility, are attracting increasing interest within the artificial intelligence medical field, particularly in the analysis of radiology reports. These present a valuable opportunity to expl...
BACKGROUND: Incidental findings of aortic aneurysms (AAs) often go unreported, and established patients are frequently lost to follow-up. Natural language processing (NLP) offers a promising solution to address these issues. While rule-based NLP meth...
RATIONALE AND OBJECTIVES: Artificial intelligence (AI) algorithms in radiology capable of detecting urgent findings have gained significant traction in recent years, but the impact of these algorithms on real-world clinical practice remains unclear w...
PURPOSE: Medical reports, governed by HIPAA regulations, contain personal health information (PHI), restricting secondary data use. Utilizing natural language processing (NLP) and large language models (LLM), we sought to employ publicly available me...