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Assessing the Utilization of Large Language Model Chatbots for Educational Purposes by Medical Teachers: A Nationwide Survey From India.
Cureus
November 2024
Physiology, All India Institute of Medical Sciences, Deoghar, Deoghar, IND.
Background Large language models (LLMs) are increasingly explored in healthcare and education. In medical education, they hold the potential to enhance learning by supporting personalized teaching, resource development, and student engagement. However, LLM use also raises concerns about ethics, accuracy, and reliance.
View Article and Find Full Text PDFUndergraduate Physiotherapists' Use of the Internet to Fulfil Their Information Needs During a Theoretical Examination: A Randomized Crossover Trial.
J Allied Health
December 2024
A308 Health Sciences Centre, University College Dublin, Belfield, Dublin 4, D04 V1W8, Ireland. Tel +35317166511.
Background: The internet is widely used by healthcare students and professionals alike to fulfil their information needs, yet limited research has utilised web log analysis to evaluate how they do so.
Aims: To elicit information needs among students via the administration of a multiple choice questionnaire (MCQ) and to evaluate how they use the internet to fulfil these needs.
Methods: Forty final-year physiotherapy students (63% female) completed a MCQ under two conditions: i) 'assisted' with internet access and ii) 'unassisted' without internet access.
Artificial Intelligence (AI) is poised to revolutionize healthcare by enhancing clinical practice, diagnostics, and patient care. Although AI offers potential benefits through data-driven insights and personalized treatments, challenges related to implementation, barriers, and ethical considerations necessitate further investigation. We conducted a cross-sectional survey using Qualtrics from October to December 2023 to evaluate U.
View Article and Find Full Text PDFArtificial intelligence in reproductive endocrinology: an in-depth longitudinal analysis of ChatGPTv4's month-by-month interpretation and adherence to clinical guidelines for diminished ovarian reserve.
Endocrine
December 2024
Department of Obstetrics and Gynecology, Liv Hospital Vadistanbul, Istanbul, Turkey.
Article Synopsis
- The study aimed to evaluate the consistency and accuracy of ChatGPTv4's responses to clinical guidelines for Diminished Ovarian Reserve (DOR) over a two-month period using a structured questionnaire.
- A variety of question types were used (open-ended, multiple-choice, true/false) and responses were rated for accuracy and completeness.
- Results showed ChatGPTv4 performed exceptionally well, achieving near-perfect accuracy, particularly in true/false questions, with significant improvements in response quality over the evaluation period.
AI chatbots show promise but limitations on UK medical exam questions: a comparative performance study.
Sci Rep
August 2024
Medical Research Platform (MRP), Giza, Egypt.
Large language models (LLMs) like ChatGPT have potential applications in medical education such as helping students study for their licensing exams by discussing unclear questions with them. However, they require evaluation on these complex tasks. The purpose of this study was to evaluate how well publicly accessible LLMs performed on simulated UK medical board exam questions.
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