Last modified: 23 Jul 2024 10:43
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 |
|
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).
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 |
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 |
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 |
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. |
Knowledge Level | Thinking Skill | Outcome |
---|---|---|
|
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 | Apply | Apply machine learning methods using R to address healthcare problems |
Procedural | Understand | Explain how machine learning is used to address healthcare problems |
Procedural | Understand | Describe the machine learning workflow |
We have detected that you are have compatibility mode enabled or are using an old version of Internet Explorer. You either need to switch off compatibility mode for this site or upgrade your browser.