As a pregnancy approaches term (the point at which the foetus is considered fully developed), decisions are made about the timing of birth and the way babies are born. These decisions are incredibly challenging for clinicians and pregnant women. Digital health records, advances in big data, machine learning and artificial intelligence methodologies, and novel data visualisation capabilities have opened up opportunities for a dynamic, ‘Learning Health System’ – where data can be harnessed to inform real-time and personalised decision-making.
Research projects in Information Technology
Displaying 91 - 100 of 188 projects.
Understanding material failure by machine learning analysis of pattern strains
Metals are made of small crystals - i.e., atoms are arranged in a particular geometric arrangement, which are typically in the range of a few 10s of microns (0.01 mm). The arrangement of these crystals greatly affects the performance of the metal and hence the performance of components where metals are used - such as in aeroplanes, gas turbine engines, cars, etc. The manner in which such materials deform, crack and fail under a variety of conditions is an important area in terms of cost and safety.
Machine learning for short message conversational analysis in Law Enforcement
This project aims to identify novel methods for inferring actors, activities, and other elements from short message communications. Covert communications are a specialist domain for analysis in the Law Enforcement (LE) context. In this project we aim to improve law enforcement’s understanding of online criminal communications, exploring texts for automated understanding of intent, sentiment, criminal capability, and involvement.
Explainability of AI techniques in law enforcement and the judiciary
This project will investigate and develop the ways in which AI algorithms and practices can be made transparent and explainable for use in law enforcement and judicial applications
Ethics of AI application in law enforcement
The use of AI in law enforcement and judicial domains requires consideration of a number of ethical issues. This project will investigate and develop frameworks that embed ethical principles in the research, development, deployment ,and use of AI systems in law enforcement (LE). A major focus is expected to concern the acquisition, use, sharing and governance of data for AI in this context.
Using 3D Printing to Improve Access to Graphics by Blind and Low Vision People
This project seeks to explore the use of 3D printing to provide better access to graphical information to those who are blind or have low vision.
Predicting fractures outcomes from clinical Registry data using Artificial Intelligence Supplemented models for Evidence-informed treatment (PRAISE) study
Project description: On behalf of the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR), we will establish the role of artificial intelligence (AI) deep learning to improve the prediction of clinical and longer-term patient-reported outcomes following distal radius (wrist) fractures. The PRAISE study will, for the first time, use a flexible three-stage multimodal deep learning fracture reasoning system to unlock important information from unstructured data sources including X-ray images, surgical and radiology text reports.
Closing the feedback loop
Student satisfaction with feedback is consistently low in higher education, and there is a lack of understanding regarding how students interpret and interact with feedback. Learning analytics promises to enhance feedback practice by providing real-time data and insights into learning behaviour and outcomes, so as to inform educational interventions. However, the feedback loop remains open without an understanding of how students make use of the received feedback or the #sustainability of such feedback practice.
Data storage to enable actionable data via quality care dashboards for clinicians
This PhD project is funded by a DHCRC project "Actionable data for clinicians and external accreditors in support of quality care provision and continuous accreditation". The successful applicant will work as part of a larger research team on this project which includes multiple industry partners.