A collection of interdisciplinary AI and data science projects in health sciences
Integrating AI, big data and smart drug design against 'Superbugs'
The World Health Organization (WHO) has identified antibiotic resistance as an urgent serious global threat, Acinetobacter baumannii is among the three WHO top-priority ‘superbugs’ against which polymyxins are the last resort and no new antibiotics will be available in the near future; however, kidney toxicity has limited the optimal use of polymyxins and resistance has emerged. This project will be the first to employ cutting-edge all-atom molecular dynamic simulations, Big Data, machine learning, and artificial intelligence to design new-generation polymyxins, and target the imperative global challenge.
Machine learning for predicting hospital-acquired complications from Electronic Medical Records
Electronic Medical Record (EMR) systems are a rich source of information that can provide life-saving insights into patients health. Despite clear evidence of the major benefits for ensuring safety and quality in the provision of health care services, EMR information is underutilised. This project harnesses the power of EMR data and Artificial Intelligence to predict various medical events in hospital-acquired complications. We develop an AI-based approach that can predict when medical interventions are not expected to improve the health of patients or may even cause them harm.
AI for older Australians in aged-care facilities: Challenges and opportunities
This project aims to identify the opportunities and challenges of using AI in aged-care facilities. It involves an analysis of the views of AI developers, aged care workers and advocates, and members of aged care residents' families. As the first cross-disciplinary analysis of the application of AI in aged-care facilities during a period of rapid change in the field, the project will provide a benchmark for future research.
Towards SDG 4: Transferring forum brain's success to health sciences and beyond
Over 100 million people learn on a Massive Open Online Course (MOOC), a powerful force for achieving widespread educational goals in SDG 4, and in every single course, an online discussion forum is used. Yet, no automated human-quality grading and feedback technology for open ended forums exists. ForumBrain AI, built by SoDa Laboratories in the Monash Business School, aims to be the solution to this problem, leveraging state of the art Natural Language Processing to make powerful and safe technology available to teachers and students alike.
Combining rapid evidence synthesis and expertise for threatened ecosystem recovery
This project is developing a novel approach to supporting evidence-based decision-making in conservation management. Drawing on tools for rapid evidence synthesis and expert consultation in the health sciences, researchers are creating a standardised approach that can efficiently identify effective management actions to address important conservation problems. Initial case studies are focused on threatened woodlands and peatlands in Australia.