Last modified: 31 May 2022 13:05
Machine learning has the potential to revolutionise healthcare. The aim of this course is to introduce machine learning for health data science with examples of real-life healthcare applications, using the popular data science language R.
| Study Type | Postgraduate | Level | 5 |
|---|---|---|---|
| Term | Second Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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This introductory course will give students from a variety of backgrounds a firm understanding of machine learning and its application to the health domain. The course will cover the foundations of machine learning; case studies of machine learning applications using health data; technical, ethical and legal challenges in the field; active areas of research in machine learning; and the machine learning workflow using R (no coding experience is required).
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 70 | |
|---|---|---|---|---|
| Assessment Weeks | 39 | Feedback Weeks | 42 | |
| Feedback |
An essay critically evaluating a published application of machine learning in healthcare |
Word Count | 3000 | |
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Evaluate | Discuss current challenges with implementing machine learning in healthcare |
| Procedural | Analyse | Relate a range of healthcare problems to appropriate machine learning algorithms |
| Procedural | Understand | Explain how machine learning is used to address healthcare problems |
| Procedural | Understand | Describe the machine learning workflow |
| Assessment Type | Summative | Weighting | 30 | |
|---|---|---|---|---|
| Assessment Weeks | 35 | Feedback Weeks | 38 | |
| Feedback |
A report explaining the choice of appropriate machine learning algorithms for example health care problems, and their implementation using R. describing the application of a suitable machine learning algorithm to address an example healthcare problem |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Analyse | Relate a range of healthcare problems to appropriate machine learning algorithms |
| Procedural | Apply | Apply machine learning methods using R to address healthcare problems |
There are no assessments for this course.
| Assessment Type | Summative | Weighting | 100 | |
|---|---|---|---|---|
| Assessment Weeks | 43 | Feedback Weeks | 46 | |
| Feedback |
A report that addresses all machine learning aspects covered in the course. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Understand | Describe the machine learning workflow |
| Procedural | Understand | Explain how machine learning is used to address healthcare problems |
| Conceptual | Evaluate | Discuss current challenges with implementing machine learning in healthcare |
| Procedural | Analyse | Relate a range of healthcare problems to appropriate machine learning algorithms |
| Procedural | Apply | Apply machine learning methods using R to address healthcare problems |
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