Dementia is one of the most common conditions in the world but until now, scientists have struggled to detect the early signs – delaying diagnosis, treatments and supports.
Researchers from the Centre for Healthy Brain Ageing (CHeBA) and the School of Computer Science and Engineering at UNSW Sydney are working on new ways to better predict and understand the onset of dementia using machine learning methodology.
Machine learning is an application of artificial intelligence that employs computer algorithms that improve automatically through experience.
Data typically collected for dementia studies arrives from a variety of different sources with different statistical properties, making it difficult to analyse at times.
But researchers hope machine learning can join the dots.
“Machine learning can give more accurate results than traditional statistical methods when modelling high-dimensional, heterogeneous, clinical data,” said PhD student Annette Spooner.
Great news.
