This narrative review evaluates the current status, potential value, key challenges, and future directions of Microsoft HoloLens 2 mixed reality (MR) technology, with a particular focus on its built-in eye tracking and visual perception functions, in...
BACKGROUND: Artificial intelligence (AI) is rapidly advancing in healthcare and has the potential to transform patient care. This study aimed to assess the knowledge, attitudes, and practices (KAP) regarding AI among pediatricians in India.
Pediatric pneumonia (PP) remains an important topic in undergraduate medical education and offers a suitable framework for evaluating large language models (LLMs) in AI-assisted learning. We developed a 27 open-ended survey including five core domain...
BACKGROUND: Pediatric drug clinical trials are essential for ensuring the accessibility and safety of medications intended for children. In recent years, the Chinese government has implemented various measures to foster the development of pediatric d...
BACKGROUND: Large language models (LLMs) demonstrate increasing potential in healthcare applications, yet their clinical utility in specialized pediatric medicine remains inadequately characterized. This study evaluated LLM performance in pediatric u...
Artificial intelligence (AI) and machine learning (ML) are rapidly transforming healthcare, with growing interest in their application to rare pediatric surgical conditions. In these settings, limited data availability often brakes traditional resear...
OBJECTIVE: Large language models (LLMs) have advanced rapidly, but their utility in pediatric surgery remains uncertain. This study assessed the performance of three AI models-DeepSeek, Microsoft Copilot (GPT-4) and Google Bard-on the European Pediat...
This text explores the integration of artificial intelligence (AI) into pediatric anesthesiology, highlighting its potential to enhance safety, efficiency, and decision-making throughout the perioperative period. It addresses the unique challenges of...
International journal of medical informatics
Jun 23, 2025
BACKGROUND: The "hallucinations" of Large Language Models (LLMs) raise concerns about their accuracy in pediatrics. This study aimed to evaluate whether integrating information from the Nelson Textbook of Pediatrics through a Retrieval-Augmented Gene...
BACKGROUND: Pediatric emergency departments face overcrowding, often driven by non-urgent consultations. Telephone triage, supported by clinical decision support systems (CDSSs), offers a potential solution to improve decision accuracy and reduce unn...
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