We look forward to participating in New Zealand’s largest digital health event, being held virtually this week on March 30-31. Our speakers’ recorded presentations are now available for you to view ahead of the live event. If you have registered for HiNZ 2022, see below for the presentation links and Q&A group session times.
Presentations and Q&A sessions
Luke Boyle, Data Scientist, presents his research on looking at new ways to measure and compare outcomes from surgery and how that has been applied to compare the DHBs. See his recording here. Q&A session: 11:30 – 12:00pm, Thursday 31st March.
Ning Hua, Data Scientist, discusses 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. See her recording here.
In her second presentation, she describes 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. See her second recording here. Q&A session: 10:40 – 11:10am, Thursday 31st March.
Enno Huang, Data Scientist, describes 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. See his recording here.
Andrew Chester, Graduate Software Engineer, discusses 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. See his recording here. Q&A session: 12:30 – 1:00pm, Thursday 31st March.
Accessing clinical data is strict and regulated due to the sensitivity and protection of privacy. Junjae Lee, Associate Product Director, talks about his team’s journey to produce a smart and efficient de-identification solution. See his recording here. Q&A session: 12:30 – 1:00pm, Thursday 31st March.
Pieta Brown, Product Director, shares 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. See her recording here. Q&A session: 10:40 – 11:10am, Thursday 31st March.
Kevin Ross, Research Director, discusses algorithm governance for the New Zealand Algorithm Hub, a national algorithm management solution that was originally launched for COVID-19. See his recording here. Q&A session: 10:40 – 11:10am, Thursday 31st March.
Other speakers we are supporting
Samuel Wong, Vensa – Telehealth as a model for health care delivery for underserved populations. See his recording here. Q&A session: 10:38 – 11:08am, Wednesday 30th March.
Yaniv Gal, Kāhu – Uncertainty in AI for skin lesion classification. When does AI lie to us? See his recording here. Q&A session: 11:30 – 12pm, Wednesday 30th March.
Thomas Adams, University of Auckland – Developing Software for Scheduling Surgeries. See his recording here. Q&A session: 12:30 – 1pm, Wednesday 30th March.
Rosie Dobson, University of Auckland – Patient perspectives on the use of health information. See her recording here. Q&A session: 10:38 – 11:08am, Wednesday 30th March.
Zhenqiang Wu, University of Auckland – Developing a Decision Support System at ED triage for predicting health outcomes. See his recording here. Q&A session: 10:40 – 11:10am, Thursday 31st March.
See the full agenda here.