Course Catalogue

AI and Software as Medical Devices BIOL5476

  • Academic Session: 2026-27
  • School: MVLS College Services
  • Credits: 20
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No
  • Collaborative Online International Learning: No
  • Curriculum For Life: No

Short Description

 This course offers a non-programmatic introduction to AI and Software used in and as a Medical Device (AIaMD & SaMD), equipping students with a foundational understanding of how these technologies operate in healthcare without requiring coding skills. Emphasis is placed on AI and software in clinical context: how it is used, interpreted, and applied in practice, through real-world case studies. Students will explore ethical implementation (including bias mitigation), and digital workflow integration aligned with current digital standards. The curriculum also introduces deployment and monitoring frameworks and ensures learners understand data protection obligations, including GDPR compliance. By the end of the course, students will be able to critically assess and support the safe, ethical, and effective adoption of AI in clinical environments.

Timetable

This course runs in Semester 2 and will be delivered in-person.

Requirements of Entry

None

Excluded Courses

None

Co-requisites

None

Assessment

1. Written assignment [25%, 1000 words] [ILOs 1-2]

2. Project output [75%, 3000 words][ILOs 1-4]

Course Aims

This course enables students to develop critical proficiency in designing and evaluating healthcare solutions with/as artificial intelligence (AI) and software systems, and their development and integration within clinical workflows without coding expertise. Learners cultivate strategic capabilities in formulating implementation approaches that address interoperability, clinician adoption, and post-deployment monitoring, while fostering responsible AI development practices essential for ethical healthcare applications.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

1. Critically analyse the technical architecture and data flow of AI and software systems in/as medical devices. 

2. Critically evaluate AI decision-making processes and clinical functionality by examining algorithm behaviour, output interpretation, and clinical utility in healthcare contexts.

3. Critically appraise AI and software development and implementation considerations including bias, safety, and post-deployment monitoring in healthcare applications.

4. Design innovative smart-device solutions by combining traditional medical device functionality with AI/software capabilities. 

Minimum Requirement for Award of Credits

No exceptions