Role of artificial intelligence (Google bard) in morphological, histopathological, and radiological image identifications: Objective Structured Practical Examination (OSPE) type-based performance.

Saudi Med J

From the Department of Physiology, College of Medicine, King Saud University (S. Meo); from the College of Medicine, Alfaisal University (AbuKhalaf, M.Z. Meo, M.O. Meo); from the Department of Science, College of Science (Ayub); from the Department of Family Medicine (ElToukhy); from the Department of Medicine (Usmani); from the Department of Surgery (Hajjar), College of Medicine, King Saud University. Riyadh, Kingdom of Saudi Arabia.

Published: May 2024

Objectives: To evaluate the role of artificial intelligence (Google Bard) in figures, scans, and image identifications and interpretations in medical education and healthcare sciences through an Objective Structured Practical Examination (OSPE) type of performance.

Methods: The OSPE type of question bank was created with a pool of medical sciences figures, scans, and images. For assessment, 60 figures, scans and images were selected and entered into the given area of the Google Bard to evaluate the knowledge level.

Results: The marks obtained by Google Bard in brain structures, morphological and radiological images 7/10 (70%); bone structures, radiological images 9/10 (90%); liver structure and morphological, pathological images 4/10 (40%); kidneys structure and morphological images 2/7 (28.57%); neuro-radiological images 4/7 (57.14%); and endocrine glands including the thyroid, pancreas, breast morphological and radiological images 8/16 (50%). The overall total marks obtained by Google Bard in various OSPE figures, scans, and image identification questions were 34/60 (56.7%).

Conclusion: Google Bard scored satisfactorily in morphological, histopathological, and radiological image identifications and their interpretations. Google Bard may assist medical students, faculty in medical education and physicians in healthcare settings.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11147552PMC
http://dx.doi.org/10.15537/smj.2024.45.5.20240141DOI Listing

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