Predictive Analytics

Big Data in Healthcare

In this research we utilise a variety of big data sources for predictive modelling in a healthcare setting. Our research aims to:

  • Develop a framework for classifying patients.
  • Develop predictive models to identify high-risk patients.
  • Develop predictive models for describing patient pathways through the healthcare system.
  • Research methods of producing information to help healthcare managers control costs.

View our projects in this theme below.

In Progress

A Deep Learning Platform for GP Referral Triage

Countering bias in the health system Heart disease is the leading cause of preventable mortality in Aotearoa, New Zealand. It is a disease that disproportionately affects certain groups such as Māori – who have higher rate of ischaemic heart disease ...
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Feasibility of Analysis of Lab Result Patterns for Patient Results

Vensa has embarked on this project to enable the analysis of laboratory result patterns that aims for faster and safer dissemination of results to patients. It addresses the problem of increasing diagnostic laboratory tests being ordered which therefore requires the ...
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nzRISK: Understanding Surgical Risk based on New Zealand’s Unique Population

Deciding whether to have major surgery can be difficult for patients and clinicians alike. The benefits and risks need to be weighed up through a shared decision-making process. This is particularly true for high-risk populations. In Aotearoa New Zealand, Māori ...
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Smart Medication Reconciliation

Automating for accuracy Patients’ regular medicines are often inaccurately prescribed when they transfer from hospital to home; a major source of medication errors and iatrogenic harm. Medicines reconciliation (MedRec) is an evidence-based process where clinicians manually compare a patient’s regular ...
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HOPE: Health Outcomes Prediction Engine

Currently, treatment decisions for elective surgery are currently based on clinicians’ assessments of the benefits the surgery will bring to ...
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Deep Representation Learning from Electronic Health Records

As Electronic Health Records (EHRs) become more ubiquitous, healthcare providers are beginning to appreciate the benefits of using this data ...
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Clinical Risk Assessments and Calculators

Recent studies have indicated that the current risk calculators are out of date and not specific to local contexts and ...
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A data mining project using the National Health and Nutrition Examination Survey dataset

Summer of Research project by Josh Atwal, supervised by Dr. Jichao Zhao (University of Auckland). Atrial fibrillation (AF) is the ...
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A Prediction Algorithm for Familial Hypercholesterolaemia in New Zealand

Summer of Research project by Nick James, supervised by Dr. Patrick Gladding (University of Auckland). Familial Hypercholesterolaemia (FH) is a ...
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Deep learning-based Melanoma prediction from skin images

Summer of Research project by Sivaram Manoharan, supervised by Bernhard Pfahringer, University of Auckland. Melanoma is an extremely dangerous type ...
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De-identification of GP e-referrals for a deep-learning based triage decision support tool

Summer of Research project by Nick James, (University of Auckland), supervised by Dr Edmond Zhang (Orion Health) and Dr Patrick ...
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