Approved Research

Artificial intelligence supported data harmonization and analysis, for the identification of prognostic factors related to balance/gait disorders and risk of falls

Lay summary

In this project we will review the UK Biobank data to find which factors or characteristics may contribute to falls or increase the risk of falls. The reason for the project is that there appears to be a gap in the scientific knowledge regarding the factors that may increase an individual's risk of falls - throught the interaction of and combined effect of the chronic conditions, psychological and behavioural factors on the individual. We aim to review medical history and the chronic conditions, as well as genetic test results and imaging from the UK Biobank data - to find out which such factors may predicit falls or poor balance which may affect balance and reduce level of activity in the individuals. In addition to reviewing the risk factors for worsening of well-being and the risk of falls, we will look at the data to find out any factors that may predict response to treatment or may cause treatment side effects, and how likely an individuals is to use new technologies for treatment (and continue with such new treatment). We also aim to find out which factors may help individuals with their balance, lower their falls risk and help them keep active. We will aim to then combine the results of the data analysis from this project with the results from other projects - including the results of data analysis from other data sets. We hope that by doing so we then be able to put together recommendations for use in clinical setting - for a better and more targeted (specific) treatment that can be offered to patients in the future.