activity
20182021
most citedPredicting Depressive Symptom Severity through Individuals' Nearby Bluetooth Devices Count Data Collected by Mobile Phones: A Preliminary Longitudinal Study

78 citations · 349 across the 18 of their papers we have counts for

collaborators
Showing 2020Show all

10 papers · 1 filter

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…

physics.soc-ph2020

Measuring the effect of Non-Pharmaceutical Interventions (NPIs) on mobility during the COVID-19 pandemic using global mobility data

Berber T Snoeijer, Mariska Burger, Shaoxiong Sun +2

The implementation of governmental Non-Pharmaceutical Interventions (NPIs) has been the primary means of controlling the spread of the COVID-19 disease. The intended effect of thes…

cs.LG2020★ 25 cited

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…

cs.LG2020★ 2 cited

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…

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.AI2020

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…

stat.AP2020★ 4 cited

Personalized acute stress classification from physiological signals with neural processes

Callum L. Stewart, Amos Folarin, Richard Dobson

Objective: A person's affective state has known relationships to physiological processes which can be measured by wearable sensors. However, while there are general trends those re…

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…

cs.IR2020★ 64 cited

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…