Dr Anton Van Der Vegt is an Advanced QLD Industry Research Fellow with the Centre for Health Services Research at UQ Faculty of Medicine. He trained as a Mechanical Engineer and Computer Scientist at University of Sydney and has worked across Australia, Europe, the US and India, designing, developing and implementing sophisticated software programs for multi-nationals as well as co-authoring two US patents. Having moved to England in 2001, he worked with several technology firms and published a book to support managers in their efforts to transform their organisations through IT. In 2005 he became the Director of Operations for a public Healthcare IT company, with budget responsibility over 100 professional staff performing electronic medical record system implementation across UK hospitals. In 2020 he gained a PhD through The University of Queensland on the application of AI with information retrieval to support clinical decision making. Since then, he has architected and managed two collaboratory projects with Queensland Health to support AI experimentation with health data. Most recently, he was awarded an Advance Queensland Industry Research Fellowship to pursue collaboratory research with Queensland Health to develop and implement AI algorithms to identify patients at risk of deterioration in hospital general wards. He is also a co-investigator on a Queensland Health sepsis prediction project.
Journal Article: Seamless EMR data access: integrated governance, digital health and the OMOP-CDM
Hallinan, Christine Mary, Ward, Roger, Hart, Graeme K., Sullivan, Clair, Pratt, Nicole, Ng, Ashley P., Capurro, Daniel, Van Der Vegt, Anton, Liaw, Siaw-Teng, Daly, Oliver, Luxan, Blanca Gallego, Bunker, David and Boyle, Douglas (2024). Seamless EMR data access: integrated governance, digital health and the OMOP-CDM. BMJ Health and Care Informatics, 31 (1) e100953, e100953. doi: 10.1136/bmjhci-2023-100953
Journal Article: Intensive care unit admission criteria: a scoping review
Soares, James, Leung, Catherine, Campbell, Victoria, Van Der Vegt, Anton, Malycha, James and Andersen, Christopher (2024). Intensive care unit admission criteria: a scoping review. Journal of the Intensive Care Society. doi: 10.1177/17511437241246901
Journal Article: Why clinical artificial intelligence is (almost) non-existent in Australian hospitals and how to fix it
van der Vegt, Anton, Campbell, Victoria and Zuccon, Guido (2023). Why clinical artificial intelligence is (almost) non-existent in Australian hospitals and how to fix it. Medical Journal of Australia. doi: 10.5694/mja2.52195
(2022–2025) Advance Queensland Industry Research Fellowships
(2022–2023) Queensland Health
Sample sub-group algorithm bias analysis for machine learning evaluation in the clinical domain
Doctor Philosophy
Methods for presenting clinical AI predictions to clinicians
Doctor Philosophy
How can we streamline the extraction and validation of data from EMRs to inform a learning health care system?
Doctor Philosophy
Seamless EMR data access: integrated governance, digital health and the OMOP-CDM
Hallinan, Christine Mary, Ward, Roger, Hart, Graeme K., Sullivan, Clair, Pratt, Nicole, Ng, Ashley P., Capurro, Daniel, Van Der Vegt, Anton, Liaw, Siaw-Teng, Daly, Oliver, Luxan, Blanca Gallego, Bunker, David and Boyle, Douglas (2024). Seamless EMR data access: integrated governance, digital health and the OMOP-CDM. BMJ Health and Care Informatics, 31 (1) e100953, e100953. doi: 10.1136/bmjhci-2023-100953
Intensive care unit admission criteria: a scoping review
Soares, James, Leung, Catherine, Campbell, Victoria, Van Der Vegt, Anton, Malycha, James and Andersen, Christopher (2024). Intensive care unit admission criteria: a scoping review. Journal of the Intensive Care Society. doi: 10.1177/17511437241246901
van der Vegt, Anton, Campbell, Victoria and Zuccon, Guido (2023). Why clinical artificial intelligence is (almost) non-existent in Australian hospitals and how to fix it. Medical Journal of Australia. doi: 10.5694/mja2.52195
van der Vegt, Anton H, Campbell, Victoria, Mitchell, Imogen, Malycha, James, Simpson, Joanna, Flenady, Tracy, Flabouris, Arthas, Lane, Paul J, Mehta, Naitik, Kalke, Vikrant R, Decoyna, Jovie A, Es’haghi, Nicholas, Liu, Chun-Huei and Scott, Ian A (2023). Systematic review and longitudinal analysis of implementing Artificial Intelligence to predict clinical deterioration in adult hospitals: what is known and what remains uncertain. Journal of the American Medical Informatics Association, 31 (2), 509-524. doi: 10.1093/jamia/ocad220
Kamel Rahimi, Amir, Ghadimi, Moji, van der Vegt, Anton H., Canfell, Oliver J., Pole, Jason D., Sullivan, Clair and Shrapnel, Sally (2023). Machine learning clinical prediction models for acute kidney injury: the impact of baseline creatinine on prediction efficacy. BMC Medical Informatics and Decision Making, 23 (1) 207, 1-14. doi: 10.1186/s12911-023-02306-0
Implementation frameworks for end-to-end clinical AI: derivation of the SALIENT framework
van der Vegt, Anton H., Scott, Ian A., Dermawan, Krishna, Schnetler, Rudolf J., Kalke, Vikrant R. and Lane, Paul J. (2023). Implementation frameworks for end-to-end clinical AI: derivation of the SALIENT framework. Journal of the American Medical Informatics Association, 30 (9), 1503-1515. doi: 10.1093/jamia/ocad088
van der Vegt, Anton H., Scott, Ian A., Dermawan, Krishna, Schnetler, Rudolf J., Kalke, Vikrant R. and Lane, Paul J. (2023). Deployment of machine learning algorithms to predict sepsis: systematic review and application of the SALIENT clinical AI implementation framework. Journal of the American Medical Informatics Association, 30 (7), 1349-1361. doi: 10.1093/jamia/ocad075
AgAsk: an agent to help answer farmer’s questions from scientific documents
Koopman, Bevan, Mourad, Ahmed, Li, Hang, van der Vegt, Anton, Zhuang, Shengyao, Gibson, Simon, Dang, Yash, Lawrence, David and Zuccon, Guido (2023). AgAsk: an agent to help answer farmer’s questions from scientific documents. International Journal on Digital Libraries. doi: 10.1007/s00799-023-00369-y
Lim, Han Chang, Austin, Jodie A., van der Vegt, Anton H., Rahimi, Amir Kamel, Canfell, Oliver J., Mifsud, Jayden, Pole, Jason D., Barras, Michael A., Hodgson, Tobias, Shrapnel, Sally and Sullivan, Clair M. (2022). Toward a learning health care system: a systematic review and evidence-based conceptual framework for implementation of clinical analytics in a digital hospital. Applied Clinical Informatics, 13 (02), 339-354. doi: 10.1055/s-0042-1743243
Do better search engines really equate to better clinical decisions? If not, why not?
van der Vegt, Anton, Zuccon, Guido and Koopman, Bevan (2021). Do better search engines really equate to better clinical decisions? If not, why not?. Journal of the Association for Information Science and Technology, 72 (2) asi.24398, 141-155. doi: 10.1002/asi.24398
How searching under time pressure impacts clinical decision making
Van der Vegt, Anton, Zuccon, Guido, Koopman, Bevan and Deacon, Anthony (2020). How searching under time pressure impacts clinical decision making. Journal of the Medical Library Association, 108 (4), 564-573. doi: 10.5195/jmla.2020.915
Learning inter-sentence, disorder-centric, biomedical relationships from medical literature
van der Vegt, Anton H., Zuccon, Guido and Koopman, Bevan (2020). Learning inter-sentence, disorder-centric, biomedical relationships from medical literature. AMIA Annual Symposium. Proceedings, 2019, 1216-1225.
van der Vegt, Anton, Zuccon, Guido, Koopman, Bevan and Deacon, Anthony (2018). The impact of a search engine on clinical decisions under time and system effectiveness constraints: research protocol. JMIR Research Protocols, 8 (5) e12803, e12803-213. doi: 10.2196/12803
A task completion framework to support single-interaction IR research
van der Vegt, Anton, Zuccon, Guido, Koopman, Bevan and Bruza, Peter (2018). A task completion framework to support single-interaction IR research. Journal of Documentation, 74 (2), 289-308. doi: 10.1108/jd-09-2017-0128
van der Vegt, Anton (2020). Minimal interaction Information Retrieval: a theoretical framework with applications in clinical decision support. PhD Thesis, School of Information Technology and Electrical Engineering, The University of Queensland. doi: 10.14264/uql.2020.888
(2022–2025) Advance Queensland Industry Research Fellowships
(2022–2023) Queensland Health
Sample sub-group algorithm bias analysis for machine learning evaluation in the clinical domain
Doctor Philosophy — Principal Advisor
Other advisors:
Methods for presenting clinical AI predictions to clinicians
Doctor Philosophy — Principal Advisor
Other advisors:
How can we streamline the extraction and validation of data from EMRs to inform a learning health care system?
Doctor Philosophy — Associate Advisor
Other advisors: