activity
20192023
most citedMedCATTrainer: A Biomedical Free Text Annotation Interface with Active Learning and Research Use Case Specific Customisation

36 citations · 78 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CL2023★ 18 cited

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…

cs.CL2021★ 5 cited

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…

cs.LG2020

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…

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

Comparative Analysis of Text Classification Approaches in Electronic Health Records

Aurelie Mascio, Zeljko Kraljevic, Daniel Bean +4

Text classification tasks which aim at harvesting and/or organizing information from electronic health records are pivotal to support clinical and translational research. However t…

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…