Visualisation, Big Data and Analytics for Health Care Data

Project Code: 4901

Faculty: Faculty of Engineering

Department: Engineering Science

Main Supervisor: Dr Cameron Walker

Application open date: 16 Jun 2014

Application deadline: 11 Mar 2015

Enrolment information: NZ Citizens, NZ Permanent Residents, International

Introduction

As health information systems become more sophisticated and data-rich, it has become harder for
users and health care organisations to derive meaningful information from the wealth (and often
over abundance) of this data. Researching and developing effective visualisation techniques is
extremely important for the future, especially the ability to deliver valuable information (rather than just "data") to clinicians.

The important problem addressed by the proposed research is the presentation of large and diverse types of healthcare data and information in a manner that conveys the highest knowledge content in the simplest and most intuitive way possible so that clinicians can effectively integrate that knowledge into their care plans to improve patient outcomes and reduce delivery costs.
The proposed project involves developing visualization techniques to aid understanding of patient data in the health system. This data will include the masses of historic data that are becoming available with the integration of existing databases, and also the new forms of big data, such as genomics data, that are becoming available due to scientific advances. This project will aim to deliver a visualization tool for allowing clinicians to easily interrogate and analyse a health database, greatly enhancing their understanding of the key factors that lead to effective care plans and assisting them in effective diagnosis.

What we are looking for in a successful applicant

Knowledge of data analysis, particularly visualisation and/or big data. Experience with programming, particularly Java.

Objective

1) Visual Exploration of Heath Data
2) Identification of Potential Visualisation, Big Data and Analytics Methods
3) Prototyping of Visualisation/Big Data/Analytics Methods
4) Implementation/Testing of Methods

Other information
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