Clinical Decision Support Guided by Risk Models in Suicide Screening: A Randomized Clinical Trial Academic Background Suicide prevention is a crucial topic in global public health, particularly in healthcare environments where identifying and intervening in suicide risks are top priorities. Traditional methods for identifying suicide risks rely mai...

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...

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...

Precision Autofocus in Optical Microscopy with Liquid Lenses Controlled by Deep Reinforcement Learning Academic Background Microscopic imaging plays a crucial role in scientific research, biomedical studies, and engineering applications. However, traditional microscopes and autofocus techniques face hardware limitations and slow software speeds in ...

Rapid 3D Imaging at Cellular Resolution for Digital Cytopathology with a Multi-Camera Array Scanner (MCAS) Academic Background Optical microscopy has long been the standard method for diagnosis in cytopathology. However, traditional whole-slide scanners, while capable of automatically imaging and digitizing large sample areas, are slow and expensiv...

Research on ECG Diagnosis Foundation Model Based on Signal-Language Architecture Academic Background Cardiovascular disease (CVD) is the leading cause of death worldwide, and early identification of high-risk populations is crucial. The electrocardiogram (ECG), a non-invasive, cost-effective, and widely used diagnostic tool, is recorded over 300 mi...