COMPUTER SCIENCE EDUCATION IN MEDICINE: A STUDENT-BASED CURRICULUM GAP ANALYSIS

Objective: Many computer science courses in medical schools at Iraqi universities still center on generic digital literacy (operating an OS, basic word processing, spreadsheets, slides) at a time when clinical work depends more and more on electronic health records, picture archiving systems, and AI-assisted diagnosis. This paper looks at one such course in detail: the Computer Science course taught to first-stage students at the College of Medicine, University of Misan, Iraq. Method: This study analyzed the course's official 2025–2026 syllabus and its current theoretical and practical teaching material, and administered a 25-item survey to 201 first- and second-stage students, comparing the findings against recent literature on digital-health competencies. Results: The 2025–2026 syllabus turned out to have been partially updated: it now formally lists Microsoft Word, Excel, and PowerPoint, and a MEDLINE/PubMed unit, as named theoretical chapters, replacing a generic closing "review" session in the earlier version. What the syllabus still does not name, despite being actively taught, are a dedicated lecture on computer-based medical systems and AI in diagnosis, a data-communication lecture, and the medical framing that several other lectures, including internet technologies and the history of computing, now carry. No chapter, formal or informal, covers programming, data analysis, or hands-on AI work. Students rated the practical exam's ability to distinguish strong from weak performers lowest of all five survey subscales (mean 2.67/5, 24.4% agreement), and rated support for curriculum modernization highest (mean 4.48/5, 87.7% agreement), with artificial intelligence in medicine the single most requested addition (48.3%). Some of the practical-laboratory materials currently in use have not kept pace with what students actually need. Novelty: Based on these findings, this paper proposes a six-domain framework: foundational digital literacy, computational thinking and introductory programming, medical informatics and health data systems, AI in medicine, medical devices and real-time systems, and an applied capstone project. The framework is built for phased adoption within the course's existing credit hours, and offered as a template other similarly placed medical schools could adapt.