North Texas Research Forum 2026
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Division
North Texas
Hospital
Medical City Arlington
Specialty
Obstetrics & Gynecology
Document Type
Poster
Publication Date
2026
Keywords
artificial intelligence, AI, graduate medical education, ACGME, internship and residency, OBGYN, obstetrics and gynecology
Disciplines
Medical Education | Medicine and Health Sciences | Obstetrics and Gynecology
Abstract
Background: Graduate medical education faculty, while responsible for overseeing the clinical training of their residents, are additionally tasked with providing effective resident education. AI offers a potential solution to enhance development and delivery of educational topics to their trainees, while decreasing the time needed to prepare formal education resources. This study aims to evaluate resident satisfaction for different learning tools generated by AI platforms while also assess their retention of clinical content.
Methods: Three topics related to menopause were identified: (1) Menopause Physiology and Diagnosis, (2) Hormonal Therapy for Treatment of Vasomotor Symptoms, and (3) Treatment of Genitourinary symptoms. Evidence-based resources (UpToDate) were selected for each of these topics and introduced into the following AI resource generators – Gamma (PowerPoint generator), Revisely (Flashcard generator), and NotebookLM (Podcast generator). Medical City Arlington OBGYN residents will be divided into three groups. Each group will be assigned different AI-generated content as it relates to each menopause topic (e.g. Group 1 – Menopause Physiology and diagnosis: flashcards, hormonal therapy for treatment of vasomotor symptoms: podcast, treatment of genitourinary symptoms: PowerPoint). After utilizing each tool, the residents will complete a 10-question quiz looking at information retention, as well as a survey to assess learner preference and engagement. These evaluations will allow for an objective measure of teaching effectiveness as well as collecting information on user experience and feedback.
Results/Conclusion: This project is planned to be implemented in February 2026. It is anticipated that results gathered from both the quizzes and survey will show that AI-generated resources are effective tools for content delivery in medical education. Additionally, it is predicted that residents will express that incorporation of AI-generated resources are beneficial and identified by learners that these are valuable tools to incorporate into their training.
Original Publisher
HCA Healthcare Graduate Medical Education
Recommended Citation
Ruggiero, Victoria; Stokes, Cameron; and Tenzel, Nicole, "Integration of AI Resources to Enhance Obstetric and Gynecology Resident Education" (2026). North Texas Research Forum 2026. 52.
https://scholarlycommons.hcahealthcare.com/northtexas2026/52