University of Twente Student Theses
Spatial epidemiology of diseases of the nervous system : A Machine Learning approach
Kotzias, Konstantinos (2021) Spatial epidemiology of diseases of the nervous system : A Machine Learning approach.
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| Abstract: | The prevalence of diseases of the nervous system has increased over the last few decades. To this end, it is of utmost importance to determine various non-clinical risk factors for such diseases, as well as the expected number of hospital admissions in any area of interest. There have been various epidemiological studies which have attempted to address the above two objectives, applying different Machine Learning techniques. However, most of them may fail to overcome common challenges of such studies. Those include handling missing values, dealing with imbalanced data or performing Regression on data where many principal assumptions are violated. Taking into account the above reasons, we propose a Machine Learning modelling process utilizing spatial analysis. It applies 4 Feature Selection algorithms to select the sociodemographic features with the greatest importance, followed by 14 variations of predictive models based on 6 Regression algorithms to predict the annual number of hospital admissions per 10,000 inhabitants in Dutch municipalities by imputing all missing data. |
| Item Type: | Essay (Master) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 02 science and culture in general |
| Programme: | Business Information Technology MSc (60025) |
| Link to this item: | https://purl.utwente.nl/essays/88771 |
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