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Purpose: Caregivers in pediatric oncology need accurate and understandable information about their child's condition, treatment, and side effects. This study assesses the performance of publicly accessible large language model (LLM)-supported tools in providing valuable and reliable information to caregivers of children with cancer.
Methods: In this cross-sectional study, we evaluated the performance of the four LLM-supported tools-ChatGPT (GPT-4), Google Bard (Gemini Pro), Microsoft Bing Chat, and Google SGE-against a set of frequently asked questions (FAQs) derived from the Children's Oncology Group Family Handbook and expert input (In total, 26 FAQs and 104 generated responses).
Usefulness of Generative Artificial Intelligence (AI) Tools in Pediatric Dentistry.
Diagnostics (Basel)
December 2024
Department of Pediatric Dentistry, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima 734-8553, Japan.
: Generative artificial intelligence (AI) such as ChatGPT has developed rapidly in recent years, and in the medical field, its usefulness for diagnostic assistance has been reported. However, there are few reports of AI use in dental fields. : We created 20 questions that we had encountered in clinical pediatric dentistry, and collected the responses to these questions from three types of generative AI.
View Article and Find Full Text PDFEvaluation of Generative Artificial Intelligence Models in Predicting Pediatric Emergency Severity Index Levels.
Pediatr Emerg Care
January 2025
University of California Davis School of Medicine, Sacramento, CA.
Objective: Evaluate the accuracy and reliability of various generative artificial intelligence (AI) models (ChatGPT-3.5, ChatGPT-4.0, T5, Llama-2, Mistral-Large, and Claude-3 Opus) in predicting Emergency Severity Index (ESI) levels for pediatric emergency department patients and assess the impact of medically oriented fine-tuning.
View Article and Find Full Text PDFPerformance of the ChatGPT-3.5, ChatGPT-4, and Google Gemini large language models in responding to dental implantology inquiries.
J Prosthet Dent
January 2025
Postdoctoral Research Associate, Division of Bone and Mineral Diseases, Department of Internal Medicine, School of Medicine, Washington University in St. Louis, St. Louis, MO; and Lecturer, Department of Orthodontics, Faculty of Dentistry, Assiut University, Assiut, Egypt.
Statement Of Problem: Artificial intelligence (AI) chatbots have been proposed as promising resources for oral health information. However, the quality and readability of existing online health-related information is often inconsistent and challenging.
Purpose: This study aimed to compare the reliability and usefulness of dental implantology-related information provided by the ChatGPT-3.
Mortality in survivors of adolescent and young adult cancer: progress and opportunities.
Lancet Public Health
January 2025
Department of Pediatrics, Duke University School of Medicine, Durham, NC, USA.
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