2 citations · 3 across the 2 of their papers we have counts for
4 papers · 1 filter
RelCAT: Advancing Extraction of Clinical Inter-Entity Relationships from Unstructured Electronic Health Records
Shubham Agarwal, Vlad Dinu, Thomas Searle +5
This study introduces RelCAT (Relation Concept Annotation Toolkit), an interactive tool, library, and workflow designed to classify relations between entities extracted from clinic…
Improving Extraction of Clinical Event Contextual Properties from Electronic Health Records: A Comparative Study
Shubham Agarwal, Thomas Searle, Mart Ratas +3
Electronic Health Records are large repositories of valuable clinical data, with a significant portion stored in unstructured text format. This textual data includes clinical event…
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…
Identifying physical health comorbidities in a cohort of individuals with severe mental illness: An application of SemEHR
Rebecca Bendayan, Honghan Wu, Zeljko Kraljevic +9
Multimorbidity research in mental health services requires data from physical health conditions which is traditionally limited in mental health care electronic health records. In t…