Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 18,311 to 18,320 of 214,278 articles

Application of artificial intelligence based on contrast-enhanced CT imaging for predicting peritoneal metastasis in patients with T3/T4 stage gastric cancer.

PloS one
Gastric cancer, prevalent in East Asia, often presents with peritoneal metastasis at diagnosis, limiting surgical options and reducing survival rates. Given the low sensitivity of current diagnostic methods, this study aimed to develop and evaluate d... read more 

Development of AI-based dopamine transporter (DAT) image generation technique using early phase [18F]-FP-CIT PET imaging.

PloS one
OBJECTIVES: To develop and validate a deep learning-based model capable of generating dopamine transporter (DAT) images from early-phase [18F]-FP-CIT positron emission tomography (PET) imaging. MATERIALS AND METHODS: Conditional generative adversaria... read more 

Explainable AI in hospital clinical decision support systems: A scoping review of healthcare professionals' perspectives.

PLOS digital health
Explainable Artificial Intelligence (XAI) has the potential to enhance clinical decision support (CDS) systems however, it remains unclear how XAI systems are perceived by healthcare professionals in hospital settings, and if new challenges arise as ... read more 

AI-guided design of efficient perovskite solar cells operationally stable at 100°C.

Science (New York, N.Y.)
Operationally stable perovskite solar cells (PSCs) have been sought after and debated since first being demonstrated. Here, we report a four-agent collaborative artificial intelligence (AI) to guide rational design of light absorbers, ultraviolet-res... read more 

Machine learning-guided risk stratification for Long QT Syndrome genetic variants with hiPSC-derived cardiomyocytes.

Cardiovascular research
AIMS: Long QT syndrome (LQTS) is a life-threatening genetic disorder characterized by prolonged QT intervals on electrocardiograms. Congenital forms are mostly associated with variants in the KCNQ1 and KCNH2 genes. Among pathogenic or likely pathogen... read more 

Evaluating the Methodological Quality of Artificial Intelligence-Assisted Systematic Reviews: Protocol for a Mixed Methods Meta-Research Study.

JMIR research protocols
BACKGROUND: Artificial intelligence (AI), including large language models (LLMs), is increasingly integrated into systematic review (SR) workflows. AI tools may accelerate searching, screening, data extraction, and reporting, but their effects on met... read more 

Use of Commercially Available Large Language Models to Generate Information Leaflets on Post-Intensive Care Syndrome: Clinical Utility Assessment.

JMIR formative research
BACKGROUND: Patients and their families without medical knowledge may find professional health care information difficult to understand. The use of large language models (LLMs) to simplify and translate complex medical content holds promise for impro... read more 

Multilevel Determinants of Engagement in Lifelong Learning in Orthodontics From Formal to AI-Supported Approaches: Development of a Conceptual Framework Through a Qualitative Study.

JMIR medical education
BACKGROUND: Lifelong learning (LLL) is increasingly important for health care professionals, particularly within the field of orthodontics, driven by emerging technologies, updated treatment techniques, and rising patient expectations. To maintain co... read more 

Multimodal Fusion of Echocardiogram Images and Electronic Medical Records for Heart Disease Screening: Retrospective Algorithm Development and Validation Study.

JMIR medical informatics
BACKGROUND: Echocardiography is a fundamental imaging modality for the diagnosis of heart disease (HD), but its interpretation remains operator-dependent and lacks standardized, data-driven decision support. Although artificial intelligence has impro... read more 

QUASAR: A Universal Autonomous System for Atomistic Simulation and a Benchmark of Its Capabilities.

Journal of chemical information and modeling
The integration of large language models (LLMs) into materials science offers a transformative opportunity to streamline computational workflows, yet current agentic systems remain constrained by rigid, carefully crafted domain-specific tool-calling ... read more