204 citations · 498 across the 20 of their papers we have counts for
4 papers · 1 filter
Multilingual Lexical Feature Analysis of Spoken Language for Predicting Major Depression Symptom Severity
Anastasiia Tokareva, Judith Dineley, Zoe Firth +19
Background: Remotely captured spoken language could provide objective, regular indicators of depression symptom severity. However, research to date has largely used non-clinical, c…
Identifying depression-related topics in smartphone-collected free-response speech recordings using an automatic speech recognition system and a deep learning topic model
Yuezhou Zhang, Amos A Folarin, Judith Dineley +25
Language use has been shown to correlate with depression, but large-scale validation is needed. Traditional methods like clinic studies are expensive. So, natural language processi…
Multi-domain Clinical Natural Language Processing with MedCAT: the Medical Concept Annotation Toolkit
Zeljko Kraljevic, Thomas Searle, Anthony Shek +15
Electronic health records (EHR) contain large volumes of unstructured text, requiring the application of Information Extraction (IE) technologies to enable clinical analysis. We pr…
MedCAT -- Medical Concept Annotation Tool
Zeljko Kraljevic, Daniel Bean, Aurelie Mascio +5
Biomedical documents such as Electronic Health Records (EHRs) contain a large amount of information in an unstructured format. The data in EHRs is a hugely valuable resource docume…