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The Artificial Intelligence Modelling Lab (AIML) engages in a range of theoretical and applied research in Artificial Intelligence (AI) and Machine Learning (ML). Particular areas of interest include interactive theorem proving, formal modelling and verification, machine learning and its combination with higher level symbolic reasoning, as well as its application to healthcare and other complex, real-world domains.

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Some of our Existing and Past External Engagements
Recent Events

Predicting brain health outcomes from objectively-assessed sleep duration in UK Biobank

Date: 14th June 2024

This presentation will presentan assessment of the feasibility of predicting brain health outcomes from sleep duration derived using accelerometery data from UK Biobank.
Speaker: Matt Whelan

Multimorbidity analysis with low condition counts: a robust Bayesian approach for small but important subgroups

Date: 3rd May 2024
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In this talk, I will briefly introduce common network science approaches to multimorbidity research, present and explain our methodological approach, and present and show how our method can be easily used by the multimorbidity community via our released software package.
Speaker: Guillermo Romero Moreno

Investigating associations between physical multimorbidity and subsequent depression via a systematic cluster analysis

Date: 3rd May 2024

In this talk, we describe our investigation of associations between physical multimorbidity and subsequent depression by performing clustering analysis upon baseline morbidity data for UK Biobank participants and then performing survival analysis to compare time to subsequent depression diagnosis.
Speaker: Lauren DeLong