Close
This module explores the fundamental principles of applied ‘machine learning’ in healthcare and biomedicine. This course has a focus on applied methods for problems in prevention, diagnosis, therapy, aetiology, and prognosis. Authentic health data and examples serve as an opportunity to explore the concepts in greater depth, raise questions, and enable participants to acquire greater understanding regarding the role of different ML-algorithms in healthcare.
Module code
CHME0018
UCL credits
15
Course Length
9 Weeks
SYNC Days
11-13 November 2020
Assessment Dates
25th November 2019
Module organisers
Dr Holger Kunz Please direct queries to courses-IHI@ucl.ac.uk
Content
- Feature vectors and multidimensional feature spaces
- K-Nearest Neighbours
- Bayesian Classifiers
- Decision Trees
- Neural Nets
- Support Vector Machines
Teaching and learning methods
Web-based distance learning in the UCL Virtual Learning Environment.
Assessment
Summative assessment: Written report worth 100% of the overall module mark.