Exploration of Gene Set Function Discovery Using Large Language Models: GPT-4 Excels Academic Background In functional genomics, gene set enrichment analysis is a critical methodology for understanding gene functions and their associated biological processes. However, existing enrichment analyses rely heavily on curated gene function databases, suc...
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 ...
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...
Potential Improvements in Lung Nodule Measurement Precision in Computed Tomography Using Artificial Intelligence Software and Its Impact on Clinical Practice - A Simulation Study Background Accurate measurement of lung nodules is crucial for the detection and management of lung cancer. Nodule size is the primary basis for risk classification in exi...
Clinical Validation of AI-based Interpretation of PD-L1 Tumor Proportion Score in Predicting Response to Immune Checkpoint Inhibitors in Non-small Cell Lung Cancer In the field of tumor treatment and diagnosis, the assessment of PD-L1 (Programmed Death-Ligand 1) Tumor Proportion Score (TPS) is a critical task, especially in predicting the response ...
AI-Assisted Radiomics Algorithm for Glioma Grading Based on Slice Pooling Background Introduction Glioma is the most common and threatening tumor in the central nervous system, characterized by high incidence, high recurrence rates, high mortality, and low cure rates. The World Health Organization (WHO) classifies gliomas into four grades (I, II, I...
Clinical Gastrointestinal Disease Screening Based on the Bionic Artificial Tentacle Method Background Gastrointestinal diseases display a wide range of complex symptoms globally, such as diarrhea, gastrointestinal bleeding, malabsorption, malnutrition, and even neurological dysfunction. These diseases pose significant health challenges and socioeco...
Utilizing Electronic Health Record Features to Identify Undiagnosed Patients with Common Subtype of Immunodeficiency Recently, Johnson and colleagues published a study titled “Electronic health record signatures identify undiagnosed patients with common variable immunodeficiency disease” in Science Translational Medicine. This research utilizes ele...