Knowledge discovery for health risk prediction

PhD Thesis


Pham, Thuan. 2020. Knowledge discovery for health risk prediction. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/jj7h-9231
Title

Knowledge discovery for health risk prediction

TypePhD Thesis
Authors
AuthorPham, Thuan
SupervisorTao, Xiahui
Zhang, Ji
Yong, Jianming
Institution of OriginUniversity of Southern Queensland
Qualification NameDoctor of Philosophy
Number of Pages190
Year2020
Digital Object Identifier (DOI)https://doi.org/10.26192/jj7h-9231
Abstract

Improving the accuracy of the diagnosis of disease can help to increase the quality of healthcare. Many researchers have developed classification models to support healthcare practitioners to make accurate diagnoses, avoiding the need to rely on their experience base diagnose diseases. However, these models are currently based on datasets collected from healthcare data including medical history. As a result, the reliability and accuracy of predicting results of the diagnosis, are limited.

Following the goal of improving the accuracy of health risk prediction, this thesis concentrates on the classification of tasks through mining healthcare data. The study suggests several frameworks and algorithms to develop classification models. In addition, challenges of extracting useful information and processing data noise from the real dataset are addressed as a way of learning models. Classification models are developed based on well-proven medical data sources. By using medical evidence, the study aims to improve the accuracy of classification for health risk prediction.

The first contribution of this thesis is an innovation of building a binary classification model to predict patients’ risks. The second contribution of this dissertation is to build a medical knowledge base to support classification models for improving the reliability and accuracy of the model. The third significant contribution of the thesis provides a framework for building a predictive model within multiple diseases.

Keywordsheterogeneous information graph, data mining, healthcare, knowledge discovery
ANZSRC Field of Research 2020420308. Health informatics and information systems
469999. Other information and computing sciences not elsewhere classified
460902. Decision support and group support systems
460308. Pattern recognition
460502. Data mining and knowledge discovery
Byline AffiliationsSchool of Sciences
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