As health data becomes increasingly high-dimensional—spanning everything from patient records to genetic and spatial data—analysts need robust tools to uncover patterns, groupings, and relationships within these complex structures. The Machine Learning AI for Health Innovation module equips students with the knowledge and practical skills to analyse, interpret, and present such data using advanced statistical and machine learning techniques.
You will explore a wide range of AI methodologies, including logistic regression, discriminant analysis, principal component analysis, cluster analysis, multilevel models, and spatial regression. You will also be introduced to modern penalised regression and machine learning approaches suited for classification and dimension reduction, with all analyses carried out using R software.
This module uses real-world health datasets and published research to help you develop practical data analysis skills alongside critical and ethical thinking. Learning is built progressively through weekly computer-based practical sessions and journal clubs, supporting you to grow in confidence with statistical methods, digital tools, and research interpretation. You will work collaboratively with peers to evaluate published studies, discuss methodological choices, and communicate complex findings clearly. Teaching and assessment are closely aligned, with feedback built into learning activities to support your development throughout the module.
Assessment reflects real professional and research tasks. In assessment 1, you will deliver a 15-minute oral presentation critically appraising the statistical methods used in an example published study (20%). In assessment 2, you will analyse a series of datasets using a variety of techniques and submit a detailed written report with critical discussion and interpretation of findings (80%). Ideal for students aiming to become applied statisticians, data scientists, or healthcare analysts, this module builds a strong foundation in both theory and application—preparing you to tackle complex, high-volume data in any professional context. This module will empower you to apply machine learning and statistical methods confidently in a variety of innovative healthcare settings.