18 citations · 30 across the 6 of their papers we have counts for
7 papers
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…
Validating transformers for redaction of text from electronic health records in real-world healthcare
Zeljko Kraljevic, Anthony Shek, Joshua Au Yeung +8
Protecting patient privacy in healthcare records is a top priority, and redaction is a commonly used method for obscuring directly identifiable information in text. Rule-based meth…
Foresight -- Generative Pretrained Transformer (GPT) for Modelling of Patient Timelines using EHRs
Zeljko Kraljevic, Dan Bean, Anthony Shek +9
Background: Electronic Health Records hold detailed longitudinal information about each patient's health status and general clinical history, a large portion of which is stored wit…
MedGPT: Medical Concept Prediction from Clinical Narratives
Zeljko Kraljevic, Anthony Shek, Daniel Bean +3
The data available in Electronic Health Records (EHRs) provides the opportunity to transform care, and the best way to provide better care for one patient is through learning from…
A Knowledge Distillation Ensemble Framework for Predicting Short and Long-term Hospitalisation Outcomes from Electronic Health Records Data
Zina M Ibrahim, Daniel Bean, Thomas Searle +7
The ability to perform accurate prognosis of patients is crucial for proactive clinical decision making, informed resource management and personalised care. Existing outcome predic…
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…