Category: Summer scholarship

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 Gladding (University of Auckland). In New Zealand, private medical information cannot be used for research except when it directly relates to treating the patient it was collected from. There are two ways to make this …

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 of skin cancer most commonly caused by exposure to UV light. The highest incidence rate of Melanoma is in Australia and New Zealand, in addition to being the fourth most common cancer diagnosed in New …

Machine readable clinical guidelines and pathways

Summer of Research project by David Bassett, supervised by Dr. Patrick Gladding (University of Auckland) There has recently been rapid growth in the use of clinical guidelines and pathways for the assessment, diagnosis and management of medical conditions. These guidelines generally contain unstructured free text and are difficult to digitise into electronic health records, limiting …

Improved planning for the scheduling of surgeries

Summer of Research project by Thomas Adams, supervised by Dr Michael O’Sullivan, University of Auckland. To better allocate resources and plan for surgeries, Counties Manukau District Health Board (CMDHB) require data-driven analysis of their surgical scheduling. This will help them to understand the effect of re-allocating surgical sessions between surgical specialties. The aim of this …

Survey of machine learning-based approaches to de-identification of medical documents

Summer of Research project by Vithya Yogarajan, supervised by Michael Mayo, University of Waikato. Protecting patient confidentiality while using medical data from electronic health records (EHRs) for research is crucial. De-identification of EHR data provides the opportunity to use the data for research without the risk of breaching patient privacy, and avoids the need for …

Using Council Data to Investigate Health Outcomes

Summer of Research project by Kaito Goto, University of Auckland, supervised by Quentin Thurier and Dan Exeter (Precision Driven Health and Orion Health). Auckland Council has a range of geospatial and infrastructure data available, which could potentially be linked with health data to provide insights. The purpose of this project was to investigate the data …

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 genetic condition which causes an increased risk of cardiovascular disease and premature death (3-4 times the risk of early death). It is estimated to affect 1:300 people in the general population of New Zealand. There …

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 most common sustained heart rhythm disturbance. At present, 25% of the New Zealand population who are 40 years old or more will experience AF in their lifetime. AF increases morbidity and mortality. The aim of …

Effects of resourcing on timely and effective care of patients in a lymphoedema clinic

Summer of Research project by Ellen Gibbs, AUT University, supervised by Sarah Marshall (AUT University). Computer models can help design specialist health clinics, giving patients the better care and using clinic resources efficiently. Ellen Gibbs created a simulation for a clinic dedicated to treating lymphoedema. Lymphoedema causes limbs to swell up with lymph fluid and …

An online system for answering medical questions

Summer of Research project by Qiming Bao, University of Auckland, supervised by Dr Jiamou Liu (University of Auckland). As demand for doctors increases, patients may be able to decrease pressure on the health system and save themselves money by getting a preliminary diagnosis from an automatic question-and-answer system. Existing online chatbots such as Buoy Health …