CS979 - Decision Support and Health Analytics
| TIMETABLE | TEACHING MATERIAL | |
| Credits | 20 | |
| Level | 5 | |
| Semester | Semester 2 | |
| Availability | Possible elective | |
| Prerequisites | N/A | |
| Learning Activities Breakdown |
| |
| Items of Assessment | 2 | |
| Assessment | One individual assignment worth 50% and a final 2-hour examination worth 50%. | |
| Lecturer | Keith Smith, Lisa McCann, Marilyn Lennon |
Aims and Objectives
The class will provide students with a robust understanding of the technologies and principles underpinning predictive modelling, complex health data visualisation, data management and GDPR, knowledge representation, and decision support systems.
Learning Outcomes
After completing this class participants will be able to:
- Know how to describe datasets in terms of their structure/format/type;
- Understand the range of techniques and technologies to aggregate, use and analyse complex healthcare data and meaningfully synthesize results;
- Understand and put into practice good principles for storing, accessing and managing data (e.g. create and use data management plans);
- Understand uses for, and challenges associated with complex data analytics (e.g. machine learning, prediction and modelling)
- Use data visualisation principles and techniques to present health and care data;
- Be able to identify and use appropriate data analytics methods and tools for a given problem using R
Syllabus
Each of the following will consist of a 2-hour lecture, with corresponding lab and personal work:
- Introduction to Analytics & Decision Support
- What is data and what does it look like?
- Accessing data and descriptive statistics
- Unsupervised machine learning
- Supervised machine learning
- Big Data in healthcare
- Data management and GDPR
- Data visualisation
- Decision support systems
- AI for decision support
- Health and care data analytics in the real world
Recommended Reading
This list is indicative only – the class lecturer may recommend alternative reading material. Please do not purchase any of the reading material listed below until you have confirmed with the class lecturer that it will be used for this class.
Healthcare Data Analytics. Reddy, C.K. and Aggarwal, C.C. Chapman and Hall / CRC Press, 2015. ISBN-13: 978-1482232110 | Stocked at Amazon (Other retailers are available)
Handbook of Medical Informatics. van Bemmel, J.H. and Musen, M.A. Springer-Verlag, Heidelberg. 1997. | Stocked at Amazon (Other retailers are available)
Last updated: 2024-08-19 13:31:40