Applying artificial intelligence in healthcare

Hosted by the AIDH WA branch (in-person)

Highly topical and moving at a rapid pace, this event asks the question: How have we been using artificial intelligence in the healthcare industry? We have a number of speakers presenting their research and experience on:

• UTI HAC Risk Prediction and Beyond

BIP-NMHS has developed a machine learning model to predict the patient’s risk of developing a healthcare associated urinary tract infection (UTI). The UTI prediction App along with the UTI prevention strategies were trialled for three months on wards G52 and G66 between March and May 2023. Preliminary results indicates a reduction of UTIs HAC by 40%. Final results will be available after the completion of the clinical coding.

• Identifying perinatal mental health risks for Aboriginal mothers using AI techniques

The use of AI and machine learning techniques, coupled with a WA-based digital screening tools to develop an intelligent risk prediction model and facilitate improved clinical decision-making in Aboriginal Perinatal Mental Health services.

• An integrated online VR platform for human-AI collaboration in digital pathology

This represents a collaboration between clinicians and AI researchers to develop useful and usable tools for pathology.

• Voice sounds and brain injury

Mild traumatic brain injury (mTBI), also known as concussion, is an important cause of morbidity and can cause cognitive, emotional, and physical symptoms. In 10-12% of individuals, mTBI symptoms will persist following the injury, taking months or years to resolve and significantly impacting the quality of life. Analysis of voice sounds may provide a non-invasive and portable diagnostic tool. AI approaches may help in the detection of the early signs of mTBI in individuals and monitor their progress in rehabilitation.

Proudly sponsored by Oqea and supported by EY.

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