A Datathon aims to bring together clinicians, data scientists, researchers and anyone interested in using data for health-related research to inform and improve outcomes.
WHO SHOULD ATTEND?
Health professionals, data scientists and engineers, academics, consumers, students, and anyone who is passionate about healthcare data, keen to learn and enjoy collaborating with like-mined people.
WHAT WILL I LEARN?
Be a part of a team to address a real clinical problem, explore methods where analysis of datasets influences clinical practice and/or health policy decisions. Strengthen collaboration across professional groups, build on shared expertise and be mentored throughout the datathon.
Participants work in a cross-disciplinary team to address a current health care problem using data analytic technologies. The datasets available may include the MIMIC Critical Care Dataset, and COVID-19 aggregated data exploring health inequities and epidemiology of COVID-19.
Teams are mentored and encouraged to complete their research project beyond attendance at the Datathon. Each team has the opportunity to present their seed research findings toward the close of the event and commendations will be awarded for the most outstanding studies.
Kick start your data science skills now, collaborate and network, and be a part of Hack Aotearoa Datathon!
Hack Aotearoa Datathon is part of a global network of events held in partnership with MIT Critical Datathon.
Datathon Leads Group
- Dr Leo Celi, MIT Critical Data
- Dr Joy Wu, Stanford Health
- Dr Mariam Pawaiz, Public Health Physician
- Dr Alex Kazemi, ANZIC/ICU
- Dr Chris Paton, Otago University
- Dr Nhung Ngiam, Otago University
DATATHON LEADS GROUP
Dr Alex Kazemi is currently a Graduate Student at the School of Population Health, University of Auckland where he is pursuing a Masters in Public Health full-time. Previously he was an Intensive Care Specialist at Middlemore Hospital, Auckland, and also has specialisation in Emergency Medicine. He is interested in global and public health, particularly data analytics for improving population health and surveillance of infectious diseases.
Dr. Binh Nguyen is a Senior Lecturer in Data Science at Victoria University of Wellington (VUW). In the past, he has won several awards for his work on the development of innovative medical devices and the application of data science to improve healthcare. Since joining VUW, he has been focusing on developing novel methods based on machine learning to solve emerging problems in health informatics, bioinformatics, and drug discovery. He was the principal investigator of a prestigious project funded by Callaghan Innovation, aimed at using deep learning approaches to develop new compounds for the treatment of B-cell malignancies. He is currently a key researcher on two research programmes funded by the Ministry of Business, Innovation and Employment about Social Services and Wellbeing (Te Rourou Tātaritang) and Data Science for Aquaculture.
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