most citedIdentifying physical health comorbidities in a cohort of individuals with severe mental illness: An application of SemEHR

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

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.CL20201 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…

cs.IR2020

The side effect profile of Clozapine in real world data of three large mental hospitals

Ehtesham Iqbal, Risha Govind, Alvin Romero +8

Objective: Mining the data contained within Electronic Health Records (EHRs) can potentially generate a greater understanding of medication effects in the real world, complementing…

cs.CL2019

Efficiently Reusing Natural Language Processing Models for Phenotype-Mention Identification in Free-text Electronic Medical Records: Methodology Study

Honghan Wu, Karen Hodgson, Sue Dyson +6

Background: Many efforts have been put into the use of automated approaches, such as natural language processing (NLP), to mine or extract data from free-text medical records to co…