Show simple item record

dc.contributor.authorEffiok, Emmanuel Eyo
dc.date.accessioned2025-09-01T08:28:34Z
dc.date.available2025-09-01T08:28:34Z
dc.date.issued2018-06-20
dc.identifier.citationEffiok, E.E.(2018) 'Lifestyle Risk Factor Modelling for Complex Disease Prediction with respect to Prostate Cancer'. MPhil Thesis. University of Bedfordshireen_US
dc.identifier.urihttp://hdl.handle.net/10547/626754
dc.description“A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Master of Philosophy”.en_US
dc.description.abstractComplex disease prediction in healthcare presents significant challenges due to the multitude of interacting risk factors and comorbidities associated with disease occurrence and prevention. Prostate cancer, as a prevalent example of a complex disease, has been shown to arise from a combination of biological, environmental, and lifestyle risk factors. While research has extensively studied individual lifestyle risk factors such as age, diet, and environmental exposures, limited attention has been given to how these factors interact when combined, particularly in the context of prostate cancer. This thesis addresses this gap by exploring the predictive impact of combined lifestyle risk factors on prostate cancer outcomes. To achieve this, a novel Predictive Algorithm Framework (PAF) is proposed, which integrates a risk factor selection and sorting algorithm adapted from the Apriori algorithm and a risk factor aggregation algorithm inspired by Opinion Geometric Pooling Algorithms. This framework facilitates the identification of significant combinations of lifestyle risk factors and estimates their influence on prostate cancer probability, offering a more nuanced understanding of how these factors interplay. Research findings demonstrate that the relationship between lifestyle risk factor combinations and prostate cancer is not linear or directly proportional. Surprisingly, certain combinations of lifestyle factors were associated with both high prevention potential and increased disease occurrence risk. This underscores the importance of targeted prevention strategies that account for the complex interplay of specific risk factor combinations. By emphasizing the nuanced impact of lifestyle risk factor modelling, this work contributes to advancing predictive methodologies for complex diseases like prostate cancer, offering actionable insights for personalized prevention strategies and improved healthcare decision-making.en_US
dc.language.isoenen_US
dc.publisherUniversity of Bedfordshireen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectlifestyle risk factorsen_US
dc.subjectprostate canceren_US
dc.subjectdisease predictionen_US
dc.subjectpredictive algorithm frameworken_US
dc.subjectcomplex disease predictionen_US
dc.titleLifestyle risk factor modelling for complex disease prediction with respect to prostate canceren_US
dc.typeThesis or dissertationen_US
refterms.dateFOA2025-09-01T08:28:35Z


Files in this item

Thumbnail
Name:
Effective Modelling of Lifestyle ...
Size:
2.564Mb
Format:
PDF
Description:
MPhil Thesis

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International