78 citations · 254 across the 11 of their papers we have counts for
12 papers
Exploring Multimodal Large Language Models for Radiology Report Error-checking
Jinge Wu, Yunsoo Kim, Eva C. Keller +7
This paper proposes one of the first clinical applications of multimodal large language models (LLMs) as an assistant for radiologists to check errors in their reports. We created…
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…
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.…
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…
Experimental Evaluation and Development of a Silver-Standard for the MIMIC-III Clinical Coding Dataset
Thomas Searle, Zina Ibrahim, Richard JB Dobson
Clinical coding is currently a labour-intensive, error-prone, but critical administrative process whereby hospital patient episodes are manually assigned codes by qualified staff f…
Comparing Natural Language Processing Techniques for Alzheimer's Dementia Prediction in Spontaneous Speech
Thomas Searle, Zina Ibrahim, Richard Dobson
Alzheimer's Dementia (AD) is an incurable, debilitating, and progressive neurodegenerative condition that affects cognitive function. Early diagnosis is important as therapeutics c…
Modeling Rare Interactions in Time Series Data Through Qualitative Change: Application to Outcome Prediction in Intensive Care Units
Zina Ibrahim, Honghan Wu, Richard Dobson
Many areas of research are characterised by the deluge of large-scale highly-dimensional time-series data. However, using the data available for prediction and decision making is h…
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…
On Classifying Sepsis Heterogeneity in the ICU: Insight Using Machine Learning
Zina Ibrahim, Honghan Wu, Ahmed Hamoud +3
Current machine learning models aiming to predict sepsis from Electronic Health Records (EHR) do not account for the heterogeneity of the condition, despite its emerging importance…
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…