Artificial Intelligence Medical Compendium

BACKGROUND: While traditional pathology supports the diagnosis and staging of colorectal cancer (CRC), computational pathology provides novel prognostic insights. Mendelian randomization (MR) is effective in uncovering causal relationships in cancer ... read more 

This study evaluates the effectiveness of large language models (LLMs), specifically Claude Sonnet 4.0 and ChatGPT 4.1, for analyzing formative feedback to support student-centered learning (SCL). In large courses, instructors often struggle to promp... read more 

PURPOSE: The aim of this study was to comparatively evaluate the responses generated by three advanced artificial intelligence (AI) models, ChatGPT-4o (OpenAI), Gemini 1.5 Flash (Google) and DeepSeek-V3, to frequently asked patient questions about me... read more 

BACKGROUND: Childhood-onset chronic nonbacterial osteomyelitis (CNO) is an inflammatory bone disease that has become better defined in the last 2 decades and is frequently encountered in pediatric rheumatology. As the disease is still not well known ... read more 

Cardiovascular and chronic disease prevention remains limited by episodic, clinic-based assessments that fail to capture physiological changes arising in daily life. As mobility constitutes one of the most stable and repetitive environments people in... read more 

Artificial intelligence (AI) is rapidly transforming the field of transfusion medicine by enhancing precision, efficiency, and safety across the transfusion continuum. This article provides a comprehensive overview of AI technologies and their applic... read more 

Certain RNAs exhibit both protein-coding and regulatory non-coding functions, termed bifunctional RNAs or coding and non-coding RNAs. Long non-coding RNAs (lncRNAs), which play crucial roles in gene regulation and cellular processes, represent a majo... read more 

Efficient molecular representations are critical for improving the performance and generalization of large language models in chemical learning. Transformer-based architectures have advanced molecular representation learning, yet capturing localized ... read more 

OBJECTIVE: This study aims to propose a multimodal, multi-view deep learning approach for breast cancer virtual biopsy, a non-invasive classification of breast lesions as malignant or benign, by integrating Full-Field Digital Mammography (FFDM) and C... read more 

PURPOSE: Collections of interesting cases are at the heart of radiology education, but efficient saving and sharing of cases has always been a challenge. While numerous home-grown teaching file systems have been created, those deeply dependent on a s... read more