HELSI Bites: Linguistic Measures for the Detection of Clinical Conditions
Linguistic Measures for the Detection of Clinical Conditions
Presented by Professor Aline Villavicencio, Chair in Natural Language Processing, The Department of Computer Science
Psycholinguistic tests have been traditionally used as one of the ways in which to assess language changes in clinical conditions like Alzheimer’s Disease. In this talk I discuss how some recent advances in natural language processing and neural network models can be used to inform the detection of clinical conditions, including one study in particular where these models were used to help distinguishing healthy controls from clinical cases with early stages of Alzheimer’s Disease and Mild Cognitive Deficits.
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