Digital Linguistic Biomarkers: Beyond Paper and Pencil Tests

Recent research has demonstrated that automatically obtainable and analysed quantitative linguistic data, extractable from a person’s verbal productions, can be useful for identifying and classifying individuals with cognitive impairments, at an early stage. Subtle language deficits can be employed as “digital linguistic biomarkers”, namely objective, quantifiable behavioral data which can be collected and measured by means of digital devices, allowing for a low-cost pathology detection, classification and monitoring. Classical pen-and-paper neuropsychological tests are costly and time consuming to process, imposing limitations since manually captured features and results can be prone to human error and bias. This Research Topic aims at bringing together research on digital linguistic biomarkers from different cognitive science subfields. We welcome original research or systematic reviews on the use of Natural Language Processing (NLP) methods and tools for e.g. clinical diagnosis, evaluation of disease severity, and prognosis.