Medical students’ perceptions of an artificial intelligence (AI) assisted diagnosing program

Abstract

As artificial intelligence (AI) assisted diagnosing systems become accessible and user-friendly, evaluating how first-year medical students perceive such systems holds substantial importance in medical education. This study aimed to assess medical students’ perceptions of an AI-assisted diagnostic tool known as ‘Glass AI.’ Data was collected from first year medical students enrolled in a 1.5-week Cell Physiology pre-clerkship unit. Students voluntarily participated in an activity that involved implementation of Glass AI to solve a clinical case. A questionnaire was designed using 3 domains: 1) immediate experience with Glass AI, 2) potential for Glass AI utilization in medical education, and 3) student deliberations of AI-assisted diagnostic systems for future healthcare environments. 73/202 (36.10%) of students completed the survey. 96% of the participants noted that Glass AI increased confidence in the diagnosis, 43% thought Glass AI lacked sufficient explanation, and 68% expressed risk concerns for the physician workforce. Students expressed future positive outlooks involving AI-assisted diagnosing systems in healthcare, provided strict regulations, are set to protect patient privacy and safety, address legal liability, remove system biases, and improve quality of patient care. In conclusion, first year medical students are aware that AI will play a role in their careers as students and future physicians.

Keywords:

• Artificial intelligence
• deep learning
• medical education
• physician workforce
• healthcare ethics

Disclosure statement

No potential conflict of interest was reported by the author(s).

Table 1. Survey results.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This research initiative was generously supported by a grant from the Mitchell Wolfson Sr Foundation.

Notes on contributors

Emely Robleto

Emely Robleto serves as a Research Associate at the University of Miami - Miller School of Medicine with a keen interest in pursuing a career in Medicine. She obtained a Master’s Degree in Biochemistry and Molecular Biology in 2022, and conducted research focused on mechanistic and molecular interaction studies related to cancer signaling. Currently, her interests involve research concerning COVID- and COVID-vaccine induced myocarditis.

Ali Habashi

Ali Habashi is Associate Professor of Professional Practice at the University of Miami. He stands out as an award-winning filmmaker and educator with a rich 25-year professional background. His commitment to education is evident in his initiation and guidance of cross-disciplinary media projects addressing critical global issues. His expertise spans a diverse array of subjects, encompassing the communication of intricate global challenges. These topics include but are not limited to climate resilience, marine conservation, access to clean drinking water and sanitation, healthcare disparities based on race/ethnicity and gender within underserved communities, and the complexities of aging in the 21st century. Additionally, Ali delves into the potential repercussions of extending human life/health span on healthcare systems, populations, resources, and generational succession.

Mary-Ann Benites Kaplan

Mary-Ann Benites Kaplan is currently Director of Transformational Learning and Assistant Professor of Professional Practice at the University of Miami. Over the course of her two-decade tenure in higher education, serving both as a faculty member and instructional designer, she has honed her skills in transformational leadership, program design, outcomes assessment, and curriculum design and development. Her primary research focuses on critical race theory and academic resilience, specifically in students of color in graduate and post-graduate education. As a proven educator, she brings expertise in teaching, advising dissertation candidates, and proficiently managing and delivering educational programs spanning various disciplines, including Health Informatics, Clinical Informatics, Higher Education Administration, Undergraduate Education, and First-year Medical Education.

Richard L. Riley

Richard L. Riley, Professor of Microbiology and Immunology and Associate Dean for Basic Science Integration at the University of Miami – Miller School of Medicine, has played an integral role in medical education. With a notable 29-year directorship for medical immunology courses, he has shaped the academic landscape. Dr. Riley’s active involvement in research, particularly in immune system dysfunction in old age and post-chemotherapy, is evident through his authorship of over 80 published articles and monographs.

Chi Zhang

Chi Zhang, is Assistant Professor of Professional Practice and Director of Program Evaluation at the University of Miami – Miller School of Medicine. With a rich background in medical education since 1993, he has worked across various institutions in continuing, graduate, and undergraduate medical education. His research interests are primarily in program evaluation and learner assessment.

Laura Bianchi

Laura Bianchi, Professor of Physiology and Biophysics at the University of Miami – Miller School of Medicine, directs the Cellular Physiology and Molecular Biophysics Graduate Program. Her research delves into ion channels and transporters and uses the namatode C. elegans as a model organism. More specifically, using genetic, molecular, imaging, and electrophysiological approaches her laboratory investigates the molecular mechanisms mediated by ion channels and transporters underlying the functional interaction between glia and neurons and how these shape animal behaviors in health, disease, and aging.

Lina A. Shehadeh

Lina A. Shehadeh, Professor of Medicine at the University of Miami – Miller School of Medicine, leads a laboratory investigating metabolic switch in Heart Failure with Preserved Ejection Fraction (HFpEF) and Sudden Death. Dr. Shehadeh’s expertise in computational biology and data mining drive her research on COVID-induced myocarditis and endothelial and immunogenic dysfunction in Long COVID. Her work involves the identification of candidate genes and microRNAs with therapeutic potential, utilizing translational tools like AAV gene therapy, RNA aptamers, and monoclonal antibodies to reverse heart failure and prevent cholesterol influx in renal tubules and cardiac myocytes. Dr. Shehadeh is active in medical education with a focus on Scholarly Research Pathways, Cell Physiology, and innovation in medical education.