The step is deemed a major advance in clinical AI design because most current AI models require laborious human annotation of vast reams of data before the labeled data are fed into the model to train it.
The researchers aim to develop a unique fully implantable Brain-Computer Interface (BCI) system for people with locked-in syndrome (LIS) - a condition in which paralysis severely limits communication.
If validated in larger studies, the approach could be used to screen for the disease in low resource settings, say the researchers.