Application of large language models in disease diagnosis and treatment.

Large language models (LLMs) such as ChatGPT, Claude, Llama, and Qwen are emerging as transformative technologies for the diagnosis and treatment of various diseases. With their exceptional long-context reasoning capabilities, LLMs are proficient in clinically relevant tasks, particularly in medical text analysis and interactive dialogue. They can enhance diagnostic accuracy by processing vast amounts of patient data and medical literature and have demonstrated their utility in diagnosing common diseases and facilitating the identification of rare diseases by recognizing subtle patterns in symptoms and test results.

An artificial intelligence system for distinguishing between gastrointestinal stromal tumors and leiomyomas using endoscopic ultrasonography.

Background: Gastrointestinal stromal tumors (GISTs) and gastrointestinal leiomyomas (GILs) are the most common subepithelial lesions (SELs). All GISTs have malignant potential; however, GILs are considered benign. Current imaging cannot effectively distinguish GISTs from GILs.

Standard Liver Volume-Predicting Formulae Derived From Normal Liver Volume in Children Under 18 Years of Age.

Standard liver volume (SLV) is important in risk assessment for major hepatectomy. We aimed to investigate the growth patterns of normal liver volume with age and body weight (BW) and summarize formulae for calculating SLV in children. Overall, 792 Chinese children (<18 years of age) with normal liver were enrolled.

Bioactivity-guided fast screen and identification of cancer metastasis chemopreventive components from raw extracts of Murraya exotica.

Murraya exotica is a traditional Chinese medicine (TCM) widely grown in southeast China. We herein proposed a fast strategy for separation and identification of active components of cancer metastatic chemopreventives from the root, leaf, twig and stem bark extracts that were obtained by reflux in 80% acidic ethanol and then liquid-liquid extraction. High performance liquid chromatography (HPLC) analysis showed that the extract mixtures from leaf, bark and twig were similar, while the root extract contained a characteristic component (CM1).