Find us at booth 30!
SURVEY OF THE DAY
Tell us what YOU think about health data research.
MEET OUR RESEARCHERS
Top minds from NZ’s health data science community will be there – do you have a project idea?
IN IT TO WIN IT
Take our survey and enter to win a super-cool anti-theft backpack.
Wednesday 21 November
Survey of the day: Would you bequeath your personal health data to science?

Dr Kevin Ross
9:00am – Session 2.4 – Room 4 Shed 6
Dramatically improving cost-effective delivery of care through machine learning models
Junjae Lee
11:20am – Session 3.7 – Room 7 Upstairs
End-to-End De-Identification Framework
Dr Kevin Ross
2:40pm – Session 4.1 – Room 1 Shed 6
Precision Driven Health Partnership Success
Randall Britten and Jens Andreas
9:20am – Session 6.6 – Room 6
Smart MedRec: Using Indirect Data Labelling for Machine Learning
Jiunn Howe Lee
9:40am – Session 6.6 – Room 6
Value Added by Applying Multiple Imputation to Real World Datasets
Farhaan Mirza and Mirza Baig
11:20am – Session 7.6 – Room 6
Predicting Hospital Admission Risk Using Primary and Secondary Data Sources
Michael Hosking
11:20am – Session 7.1 – Room 1
Clinical Document Semantic Search: A User-centred Approach to Clinical Information Seeking
Mirza Baig
12:00pm – Session 7.6 – Room 6
Measuring the Accuracy of Patients at Risk of Hospital Readmission
Samuel Wong
12:00pm – Session 7.1 – Room 1
Analysis of Laboratory Result Patterns for Patient Alerts on vensa.com
Luke Boyle
1:30pm – Session 8.7 – Room 7
Using Machine Learning to Improve Surgical Risk Prediction in High Risk Subspecialty Patient Cohorts in New Zealand
Luke Boyle for Edmond Zhang
appx 2:45pm – Session 8.6 – Room 6
A Deep Learning Platform for GP Referral Triage
Luke Boyle for Quentin Thurier
appx 2:50pm – Session 8.6 – Room 6
Interpretable Machine Learning for Healthcare
Jiunn Howe Lee for Stephen Connor
1:30pm – Session 8.7 – Room 7
Scalability of Multiple Imputation of Missing Health Data
Mirza Baig for Reece Robinson
2:15pm – Session 8.7 – Room 7
A Public Website for Kiwis – An Authentic Web Library of Clinical Risk Assessments, Algorithms, Tools, Calculators and Predictive Machine Learning Models
Mirza Baig
appx 2:30pm – Session 8.7 – Room 7
Clinician-centred Mobile Application Design Framework and Clinical Decision Support for Hospitals