Textual Proficiency and Visual Deficiency: A Comparative Study of Large Language Models and Radiologists in MRI Artifact Detection and Correction.

Rationale And Objectives: To assess the performance of Large Language Models (LLMs) in detecting and correcting MRI artifacts compared to radiologists using text-based and visual questions.

Materials And Methods: This cross-sectional observational study included three phases. Phase 1 involved six LLMs (ChatGPT o1-preview, ChatGPT-4o, ChatGPT-4V, Google Gemini 1.

Percutaneous cholecystostomy in elderly patients with acute cholecystitis: Factors influencing mortality, morbidity, and length of hospital stay.

Background: Acute cholecystitis (AC) is increasingly common and imposes a burden on healthcare systems, particularly in the elderly population. While laparoscopic cholecystectomy (LC) is the definitive treatment, percutaneous cholecystostomy (PC) is often preferred based on various factors. The treatment of elderly patients requires a multidisciplinary approach that carefully assesses surgical risks due to age-related changes and comorbidities.

Thalamo-insular cortex connections in the rat and human.

The insular cortex (ICx) has a role in large a variety of functions. Thalamus plays an important role in modulating cortical functions. The present study aims to show thalamic-ICx connections using the fluoro-gold (FG) tracing method in rats and diffusion tensoring-based tractography (DTI) in humans.

Juvenile papillomatosis: A case report.

Juvenile papillomatosis (JP) is a very rare benign proliferative breast disease, especially in young women under 30 years of age. Its etiology is not clear yet. Although some patients have breast cancer in their family history, up to 10% breast cancer can develop in the follow-up of JP patients.

The Diagnostic Performance of Large Language Models and General Radiologists in Thoracic Radiology Cases: A Comparative Study.

Purpose: To investigate and compare the diagnostic performance of 10 different large language models (LLMs) and 2 board-certified general radiologists in thoracic radiology cases published by The Society of Thoracic Radiology.

Materials And Methods: We collected publicly available 124 "Case of the Month" from the Society of Thoracic Radiology website between March 2012 and December 2023. Medical history and imaging findings were input into LLMs for diagnosis and differential diagnosis, while radiologists independently visually provided their assessments.

Evaluating text and visual diagnostic capabilities of large language models on questions related to the Breast Imaging Reporting and Data System Atlas 5 edition.

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 radiology in text-based and visual questions.

Methods: This cross-sectional observational study involved two steps. In the first step, we compared ten LLMs (namely ChatGPT 4o, ChatGPT 4, ChatGPT 3.

Can large language models be new supportive tools in coronary computed tomography angiography reporting?

The advent of large language models (LLMs) marks a transformative leap in natural language processing, offering unprecedented potential in radiology, particularly in enhancing the accuracy and efficiency of coronary artery disease (CAD) diagnosis. While previous studies have explored the capabilities of specific LLMs like ChatGPT in cardiac imaging, a comprehensive evaluation comparing multiple LLMs in the context of CAD-RADS 2.0 has been lacking.

Comparison of Performance of Large Language Models on Lung-RADS Related Questions.

This study evaluates LLM integration in interpreting Lung-RADS for lung cancer screening, highlighting their innovative role in enhancing radiological practice. Our findings reveal that Claude 3 Opus and Perplexity achieved a 96% accuracy rate, outperforming other models.

The Relationship Between Intramural Fat Accumulation and Sarcopenia on MR Enterography Exams in Patients with Crohn's Disease.

Research on magnetic resonance enterography (MRE) and sarcopenia for assessing Crohn's disease (CD) is growing. Our study examined the connections between the presence of sarcopenia, intramural fat accumulation (IFA), and clinical, laboratory, and MRE findings.This retrospective study was conducted on 112 patients with suspected or diagnosed CD who underwent 3-tesla MRE.

Optimizing Diagnostic Performance of ChatGPT: The Impact of Prompt Engineering on Thoracic Radiology Cases.

Background Recent studies have highlighted the diagnostic performance of ChatGPT 3.5 and GPT-4 in a text-based format, demonstrating their radiological knowledge across different areas. Our objective is to investigate the impact of prompt engineering on the diagnostic performance of ChatGPT 3.

Effects of laparoscopic sleeve gastrectomy on thyroid hormones and relationship between metabolic parameters and long-term total weight loss.

Background: Bariatric surgery has significant effects on metabolic parameters and hormone levels. However, the specific impact of laparoscopic sleeve gastrectomy (LSG) on thyroid hormones and other metabolic parameters remains unclear. This study aimed to investigate the short and long-term effects of LSG on thyroid hormone levels, HbA1c, and other metabolic parameters.

Symptom Duration and Surgeon Volume: Impact on Early Laparoscopic Cholecystectomy for Acute Cholecystitis.

Background: The 'golden 72 hours' rule from the onset of symptoms still applies in laparoscopic cholecystectomy for acute cholecystitis. This rule has been discussed with increasing experience in laparoscopic surgery in recent years.

Objective: This study aims to determine the optimal symptom duration based on the surgeon's volume when deciding on early laparoscopic cholecystectomy for acute cholecystitis.