Performance of Large Language Models in Radiology Image Interpretation: A Comparative Study with Human Readers Academic Background In recent years, large language models (LLMs) have demonstrated powerful capabilities in various fields, particularly in natural language processing. With the development of multimodal LLMs, these models can now handle ...

Deep Learning Algorithms in Breast Cancer Screening Academic Background Breast cancer is one of the most common cancers among women worldwide, and early screening is crucial for improving cure rates. Traditional Computer-Aided Detection (CAD) systems have been widely used in mammographic screening, particularly in the United States. However, while ...

Capability of Large Language Models in Translating CT and MRI Free-Text Radiology Reports Academic Background In the context of globalization, the increasing mobility of patients necessitates the translation of radiology reports, which are essential tools for disease diagnosis and management, into various languages. However, language barriers can i...

Changes in Reader Performance During Sequential Reading of Breast Cancer Screening Digital Breast Tomosynthesis Examinations Academic Background Breast cancer is one of the most common cancers among women worldwide, and early screening is crucial for improving cure rates. Traditional digital mammography (DM) is the primary tool for breast cancer sc...

Feasibility of Myocardial Late Gadolinium Enhancement MRI at 5T versus 3T for Myocardial Fibrosis Assessment Academic Background Myocardial fibrosis is a common pathological feature of various cardiac diseases, and accurate assessment of myocardial fibrosis is crucial for diagnosis, treatment, and prognosis. Cardiac magnetic resonance imaging (MRI)...

The Impact of AI Explanation Types on Physician Diagnostic Performance and Trust Academic Background In recent years, the development of artificial intelligence (AI) diagnostic systems in healthcare and radiology has progressed rapidly, particularly in assisting overburdened healthcare providers, showcasing the potential to improve patient care. As...

The Potential of GPT-4 in Chest Radiograph Evaluation: A Retrospective Study Academic Background In recent years, artificial intelligence (AI) has been increasingly applied in the medical field, particularly in radiology. The introduction of AI tools is transforming clinical practice, especially in imaging diagnostics. However, the widespread adopt...

Quantitative Assessment of Large Vision-Language Models in Radiology: GPT-4V’s Multimodal and Multi-Anatomic Region Capabilities Academic Background In recent years, large language models (LLMs) such as OpenAI’s ChatGPT have made significant progress in text generation. These models, based on the Transformer architecture and trained on massive amou...

Diagnostic Accuracy of CT for the Detection of Hepatic Steatosis: A Systematic Review and Meta-Analysis Academic Background Hepatic steatosis is the result of the abnormal accumulation of triglycerides in hepatocytes, which can initiate a cascade of inflammatory responses, referred to as steatotic liver disease (SLD). Metabolic dysfunction–associat...

Assessment of Nonmass Lesions Detected with Screening Breast US Based on Mammographic Findings Academic Background Breast cancer is one of the most common malignant tumors among women worldwide, and early detection and diagnosis are crucial for improving patient survival rates. Breast ultrasound (US), as a non-invasive and radiation-free imaging mo...