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Evaluation of Chatbots in the Emergency Management of Avulsion Injuries.
Dent Traumatol
January 2025
Department of Paediatric Dentistry, Faculty of Dentistry, Mersin University, Mersin, Turkey.
Background: This study assessed the accuracy and consistency of responses provided by six Artificial Intelligence (AI) applications, ChatGPT version 3.5 (OpenAI), ChatGPT version 4 (OpenAI), ChatGPT version 4.0 (OpenAI), Perplexity (Perplexity.
View Article and Find Full Text PDFComparing the performance of ChatGPT and ERNIE Bot in answering questions regarding liver cancer interventional radiology in Chinese and English contexts: A comparative study.
Digit Health
January 2025
Department of Interventional Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Introduction: This study aims to critically assess the appropriateness and limitations of two prominent large language models (LLMs), enhanced representation through knowledge integration (ERNIE Bot) and chat generative pre-trained transformer (ChatGPT), in answering questions about liver cancer interventional radiology. Through a comparative analysis, the performance of these models will be evaluated based on their responses to questions about transarterial chemoembolization and hepatic arterial infusion chemotherapy in both English and Chinese contexts.
Methods: A total of 38 questions were developed to cover a range of topics related to transarterial chemoembolization (TACE) and hepatic arterial infusion chemotherapy (HAIC), including foundational knowledge, patient education, and treatment and care.
Chatbot-delivered mental health support: Attitudes and utilization in a sample of U.S. college students.
Digit Health
January 2025
Department of Psychology, The Pennsylvania State University, University Park, PA, USA.
Objective: Chatbots' rapid advancements raise the possibility that they can be used to deliver mental health support. However, public utilization of and opinions toward chatbots for mental health support are poorly understood.
Methods: Survey study of 428 U.
A randomised cross-over trial assessing the impact of AI-generated individual feedback on written online assignments for medical students.
Med Teach
January 2025
Institute of Medical Education, University Hospital Bonn, Bonn, Germany.
Purpose: Self-testing has been proven to significantly improve not only simple learning outcomes, but also higher-order skills such as clinical reasoning in medical students. Previous studies have shown that self-testing was especially beneficial when it was presented with feedback, which leaves the question whether an immediate and personalized feedback further encourages this effect. Therefore, we hypothesised that individual feedback has a greater effect on learning outcomes, compared to generic feedback.
View Article and Find Full Text PDFCurrent Practices and Perspectives of Artificial Intelligence in the Clinical Management of Eating Disorders: Insights From Clinicians and Community Participants.
Int J Eat Disord
January 2025
SEED Lifespan Strategic Research Centre, School of Psychology, Faculty of Health, Deakin University, Geelong, Victoria, Australia.
Objective: Artificial intelligence (AI) could revolutionize the delivery of mental health care, helping to streamline clinician workflows and assist with diagnostic and treatment decisions. Yet, before AI can be integrated into practice, it is necessary to understand perspectives of these tools to inform facilitators and barriers to their uptake. We gathered data on clinician and community participant perspectives of incorporating AI in the clinical management of eating disorders.
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