What we will be presenting at the HiNZ 2022 Conference
We are excited to participate in New Zealand’s largest digital health event, which will be held virtually on March 30-31 this year. Each of our speakers will provide information and updates on our solutions, and how they continue to help improve health outcomes for our citizens. We look forward to seeing you there!
What will each of our subject experts be talking about?
Luke Boyle, Data Scientist, will present his research on looking at new ways to measure and compare outcomes from surgery and how that has been applied to compare the DHBs
Ning Hua, Data Scientist, will discuss how incremental machine learning can be set up to rank the priority of GP referrals, as well as how the model outperforms a traditional static model by handling the changing nature of the data in a clinical setting. In her second presentation, she will describe how to evaluate the potential influence of a machine learning model in referral prioritisation workflows using mathematical simulations, before implementing and integrating the model in the real world.
Enno Huang, Data Scientist, will describe how his team uses machine learning and SNOMED CT terms to enhance clinical information retrieval and how natural language processing (NLP) helps clinicians search for information among massive medical documents based on semantic meanings.
Andrew Chester, Graduate Software Engineer, will discuss his PDH-funded research on the effects of data de-identification on fairness bias, including the impacts of different levels and methodologies of de-identification.
Accessing clinical data is strict and regulated due to the sensitivity and protection of privacy. Junjae Lee, Associate Product Director, will talk about his team’s journey to produce a smart and efficient de-identification solution.
Pieta Brown, Product Director, will share key insights from a study of clinical risk prediction in the New Zealand Health sector, and share a roadmap for safe and effective algorithm use and adoption.
Kevin Ross, Research Director, will discuss algorithm governance for the New Zealand Algorithm Hub, a national algorithm management solution that was originally launched for COVID-19.
Other speakers we are supporting
- Samuel Wong, Vensa
- Yaniv Gal, Kāhu
- Sam MacNamara, Kāhu
- Thomas Adams, University of Auckland
- Zhenqiang Wu, University of Auckland
- Rosie Dobson, University of Auckland
Find out more about the HiNZ Digital Health Conference here.