A new study by researchers from the Neurosciences Research Centre at St George’s has identified the strengths and limitations of different tasks used to detect the early signs of Alzheimer’s disease through speech analysis and machine learning. Published in the journal Frontiers in Computer Science, the study demonstrates that while machine learning can be used to assess speech patterns for signs of disease, the specific task assigned to the person being tested plays a critical role in test accuracy.