activity
20192025
most citedDischarge Summary Hospital Course Summarisation of In Patient Electronic Health Record Text with Clinical Concept Guided Deep Pre-Trained Transformer Models

50 citations · 134 across the 9 of their papers we have counts for

collaborators
Showing cs.CLShow all

6 papers · 1 filter

cs.CL2025★ 1 cited

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…

cs.CL2024★ 2 cited

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…

cs.CL2022★ 50 cited

Discharge Summary Hospital Course Summarisation of In Patient Electronic Health Record Text with Clinical Concept Guided Deep Pre-Trained Transformer Models

Thomas Searle, Zina Ibrahim, James Teo +1

Brief Hospital Course (BHC) summaries are succinct summaries of an entire hospital encounter, embedded within discharge summaries, written by senior clinicians responsible for the…

cs.CL2021★ 17 cited

Estimating Redundancy in Clinical Text

Thomas Searle, Zina Ibrahim, James Teo +1

The current mode of use of Electronic Health Record (EHR) elicits text redundancy. Clinicians often populate new documents by duplicating existing notes, then updating accordingly.…

cs.CL2020

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…

cs.CL2020★ 1 cited

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…