Technical expertise and advice on Machine Learning and its application to Healthcare Data

Project Member(s): Long, G., Jiang, J., Peng, X.

Funding or Partner Organisation: Commonwealth Department of Health and Aged Care (Commonwealth Department Health and Ageing Partnership Fund - Commonwealth Competitive)
Commonwealth Department of Health and Aged Care (Commonwealth Department Health and Ageing Partnership Fund - Commonwealth Competitive)

Start year: 2019

Summary: The aim of this project is to provide the department with technical expertise and assistance in the use of machine learning on health-related data, specifically in relation to the Healthy Mind, Health Body project funded by Data Integration Partnership Australia in 2019-20.

Publications:

Gerrard, L, Peng, X, Clarke, A, Schlegel, C & Jiang, J 1970, 'Predicting Outcomes for Cancer Patients with Transformer-Based Multi-task Learning', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer International Publishing, pp. 381-392.
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Wang, Y, Peng, X, Clarke, A, Schlegel, C & Jiang, J 1970, 'Machine Teaching-Based Efficient Labelling for Cross-unit Healthcare Data Modelling', AI 2021: Advances in Artificial Intelligence, Springer International Publishing, pp. 320-331.
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Gu, P, Wu, T, Zou, M, Pan, Y, Guo, J, Xiahou, J, Peng, X, Li, H, Ma, J & Zhang, L 2020, 'Multi-Head Self-Attention Model for Classification of Temporal Lobe Epilepsy Subtypes', Frontiers in Physiology, vol. 11.
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Peng, X, Long, G, Shen, T, Wang, S & Jiang, J 1970, 'Self-Attention Enhanced Patient Journey Understanding in Healthcare System', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), Springer International Publishing, Ghent Belgium, pp. 719-735.
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FOR Codes: Health Education and Promotion, Adaptive Agents and Intelligent Robotics, Intelligent robotics

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.