Predictive disease modelling using Big data analytics and Complex network methods

Summary

This research project aims to mine administrative claim dataset to develop predictive models for individual chronic disease as well as for the comorbidity of multiple chronic diseases. For this purpose, it will use techniques and methods from Big data analytics and Complex network.

Supervisor(s)

Dr Shahadat Uddin

Research Location

Civil Engineering

Program Type

Masters/PHD

Synopsis

Chronic diseases and their subsequent tendency in developing comorbid conditions are a significant health concern worldwide. Apart from causing premature mortality and reduced quality of life, these diseases exert a significant ongoing treatment cost which impacts on national economies. Prevention of chronic diseases has been a major challenge since patients, in many cases, remain unware of the progression until they are admitted to a hospital. On the other side, administrative claim dataset is the single largest source of over time utilisation data for different healthcare services. This type of datasets has already gained wide attention for research investigation purposes since they cover a wide variety of medical services and a broad geographic area. Using big data analytics and complex network methods, this research project will mine administrative claim data to develop models for the predictive nature of different chronic diseases and their tendency of developing comorbid conditions.

Additional Information

  • Use of research technique / methodology / technology
Big data analytics and Complex network methods
  • Eligibility criteria / candidate profile
Need to have a good background in data analytics

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Keywords

Disease modelling; Big data analytics; Complex network methods and Administrative claim dataset

Opportunity ID

The opportunity ID for this research opportunity is: 2355

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