64 citations · 83 across the 6 of their papers we have counts for
7 papers
Development of a Knowledge Graph Embeddings Model for Pain
Jaya Chaturvedi, Tao Wang, Sumithra Velupillai +2
Pain is a complex concept that can interconnect with other concepts such as a disorder that might cause pain, a medication that might relieve pain, and so on. To fully understand t…
Identifying Mentions of Pain in Mental Health Records Text: A Natural Language Processing Approach
Jaya Chaturvedi, Sumithra Velupillai, Robert Stewart +1
Pain is a common reason for accessing healthcare resources and is a growing area of research, especially in its overlap with mental health. Mental health electronic health records…
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…
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…
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…
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…
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…