Parkinson’s disease is a significant health concern with profound impacts on individuals, the healthcare system and broader society. The current diagnosis model, which heavily relies on a medical professional interpreting data, often means the disease is nearly always diagnosed in the later stages, where more care and support is needed. Victoria University (VU) researcher is determined to improve the diagnostic process.
“Our interest in using AI as a diagnostic tool stems from the recognition of its potential to revolutionise healthcare by providing faster, more accurate, and cost-effective diagnoses. AI has shown remarkable capabilities in analysing complex datasets like as electroencephalogram (EEG) data quickly, automatically and accurately, making it ideal for medical applications such as diagnosing diseases.
“By developing advanced AI-based techniques, we aim to enhance early detection and ultimately improve the management of this devastating condition,” Dr Siuly said.
Her research using an AI-based technique to analyse EEG (an important tool in the diagnosing of Parkinson’s) data, showed more accurate and efficient detection of the disease as compared with traditional visual inspection methods currently used by medical professionals.
The is a proof of concept and now the real work begins to design the software in conjunction with healthcare and software partners. It’s hoped this software can be adapted for use in other neurological disorders that rely on EEG data for diagnoses including Alzheimer’s disease, mild cognitive impairment and autism.
“This is a dynamic area of research and has the potential to revolutionise how we detect and treat significant health challenges,” Dr Siuly added.
