student profile: Mr Md Ekramul Hossain


Map

Thesis work

Thesis title: Predictive modelling of the comorbidity of chronic diseases: A network approach

Supervisors: Shahadat UDDIN , Petr MATOUS

Thesis abstract:

Chronic diseases and conditions have become the leading causes of death in most countries. Due to this, governments all over the world are concerned about the chronic diseases. They become very expensive (in term of treatment cost) and bring severe health risk when patients suffer from more than one chronic disease appears at the same time (also named as comorbidity of chronic disease). Therefore, comorbidity of chronic disease management and prevention has been a major challenge for governments and related international organisations. Traditional methods of clinical diagnosis and regular monitoring of a large population are resource-intensive in term of the availability of clinical provisions and economic capability. However, the management and prevention of comorbidity of chronic diseases could lead to the development of several prediction procedures using the data mining approach applying on the hospital admission data. In this thesis, a network-based prediction model that exploits past medical history of single-chronic patients to predict their risk of developing other (chronic) disease(s) in future will be developed. Two broad goals of this work are: (1) to understand and represent the progression of chronic disease; and (2) to develop a model based on this understanding to predict the comorbidity of chronic disease for chronic disease patients. The proposed network-based prediction model could be useful for stakeholders including governments and health insurers to identify cohorts of patients at high risk of developing more than one chronic disease.

Note: This profile is for a student at the University of Sydney. Views presented here are not necessarily those of the University.