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Determinants of knowledge of preconception care among healthcare providers in Ethiopia: a systematic review and meta-analysis.
BMJ Open
January 2025
Department of Nursing, College of Health science, Ambo University, Ambo, Ethiopia.
Objective: To assess the determinants of knowledge of preconception care (PCC) among healthcare providers in Ethiopia.
Design: Systematic review and meta-analysis.
Data Source: Comprehensive literature searches were conducted in PubMed, Scopus and Health Internetwork Access to Research Initiative (HINARI) published until 20 March 2024.
QUEST-AI: A System for Question Generation, Verification, and Refinement using AI for USMLE-Style Exams.
Pac Symp Biocomput
December 2024
Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
The United States Medical Licensing Examination (USMLE) is a critical step in assessing the competence of future physicians, yet the process of creating exam questions and study materials is both time-consuming and costly. While Large Language Models (LLMs), such as OpenAI's GPT-4, have demonstrated proficiency in answering medical exam questions, their potential in generating such questions remains underexplored. This study presents QUEST-AI, a novel system that utilizes LLMs to (1) generate USMLE-style questions, (2) identify and flag incorrect questions, and (3) correct errors in the flagged questions.
View Article and Find Full Text PDFPerformance of GPT-3.5 and GPT-4 on the Korean Pharmacist Licensing Examination: Comparison Study.
JMIR Med Educ
December 2024
Research Institute of Pharmaceutical Sciences, College of Pharmacy, Chung-Ang University, Seoul, Republic of Korea.
Background: ChatGPT, a recently developed artificial intelligence chatbot and a notable large language model, has demonstrated improved performance on medical field examinations. However, there is currently little research on its efficacy in languages other than English or in pharmacy-related examinations.
Objective: This study aimed to evaluate the performance of GPT models on the Korean Pharmacist Licensing Examination (KPLE).
Evaluation of a Large Language Model on the American Academy of Pediatrics' PREP Emergency Medicine Question Bank.
Pediatr Emerg Care
December 2024
Divisions of Health Informatics and Emergency Medicine, Department of Pediatrics, University of Pittsburgh School of Medicine and UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA.
Background: Large language models (LLMs), including ChatGPT (Chat Generative Pretrained Transformer), a popular, publicly available LLM, represent an important innovation in the application of artificial intelligence. These systems generate relevant content by identifying patterns in large text datasets based on user input across various topics. We sought to evaluate the performance of ChatGPT in practice test questions designed to assess knowledge competency for pediatric emergency medicine (PEM).
View Article and Find Full Text PDFCorrection: Credentialed pharmacist-led home medicines reviews targeting treatable traits and their impact on health outcomes in people with chronic obstructive pulmonary disease: a pre- and post-intervention study.
Int J Clin Pharm
November 2024
Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Parkville, VIC, Australia.
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