Postgraduate taught 

Digital Cancer Technologies MSc

Artificial Intelligence in Cancer Research BIOL5405

Artificial Intelligence in Cancer Research BIOL5405

  • Academic Session: 2023-24
  • School: School of Cancer Sciences
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No

Short Description

This course will equip students with knowledge in basic tissue pathology in cancer, tissue histopathology techniques and governance in human tissue research. Student will learn how to identify tumour cell structures and to understand the theory behind various pathology techniques. They will also learn about different model systems and how they are utilized in research.


Teaching takes place over 3 weeks in Semester 2 with students attending lectures, seminars and tutorials.

Excluded Courses





1. Compile 3 annotated bibliographies (33.33% weighting each) ILO1-3

Course Aims

This course aims to:

  • Introduce students to the applications and ethical implications of utilizing artificial intelligence in cancer research.
  • Provide understanding of integration of big data and analysis with AI, and clinical use of AI for image analysis.
  • Provide a critical appreciation for the range of AI applications available to the field of cancer research.

Intended Learning Outcomes of Course

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

1. Critically discuss available platforms, including their application and limitations, and reflect on the difference between machine learning and AI.

2. Apply knowledge of AI platforms to critically evaluate their uses in image vs data analysis.

3. Critically evaluate the current uses of AI in cancer research and the ethical considerations associated with their use.

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course’s summative assessment.