Author: Edmond Zhang

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 …

Clinical abbreviations detection and normalisation

Summer of Research project by Enno Huang, University of Auckland, supervised by Edmond Zhang (Orion Health and Precision Driven Health) and Yun Sing Koh (University of Auckland). “2 yo F here for an RPE w/a recent URI who c/o ear pain y/d.” If you can’t understand that sentence from a real paediatric note, you are …

Evaluating Biomedical Word Embeddings

Summer of Research project by student Aaron Zhang (The University of Auckland), supervised by Dr Edmond Zhang (Orion Health). It takes time and money to train specialist medical algorithms, and medical-specific data is hard to obtain for research, but the payoff may well be worth it. Aaron Zhang’s research shows machine learning algorithms based on …

Feature importance for adverse drug event named entity recognition

Summer of Research project by Hamish Huggard, University of Auckland, supervised by Dr Edmond Zhang (Precision Driven Health and Orion Health). Automatically identifying drug names, dosages and effects in health records could help researchers find relationships between certain medications and negative effects on patients. An adverse drug event (ADE) is when something bad happens to …

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 which disproportionately affects certain groups such as Māori – who have higher rates of ischaemic heart disease (or coronary heart disease) and stroke but have lower access to health care. It is …

Smart Search: Clinical Document Semantic Search

A ‘Google’ for Electronic Health Records  Ten minutes can be an eternity for medical professionals that need to make split-second decisions to save lives. If they miss a single piece of vital information it could prove critical – but equally, if they waste precious time searching for data, that too can be damaging to the …

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 for ‘secondary applications’, such as disease diagnosis and readmission prediction, by applying machine learning techniques (in particular, deep neural networks). The difficulty with this approach is that data from EHRs is often inconsistent, episodic, exists …