Area of research
Artificial Intelligence · Molecular Biology
Research interest
Research interests include Biomedical Text Mining and Ontologies, Machine Learning in Healthcare, Topic Modeling, and Mental Health via Writing.
EHR-based prediction modelling meets multimodal deep learning: A systematic review of structured and textual data fusion methods
What is the patient re-identification risk from using de-identified clinical free text data for health research?
Situating emotion regulation in autism and ADHD through neurodivergent adolescents’ perspectives
Question answering systems for health professionals at the point of care—a systematic review
Trustworthy Data and AI Environments for Clinical Prediction: Application to Crisis-Risk in People With Depression
Unraveling ethnic disparities in antipsychotic prescribing among patients with psychosis: A retrospective cohort study based on electronic clinical records
Predicting type 2 diabetes prevalence for people with severe mental illness in a multi-ethnic East London population
Understanding Views Around the Creation of a Consented, Donated Databank of Clinical Free Text to Develop and Train Natural Language Processing Models for Research: Focus Group Interviews With Stakeholders
A survey on clinical natural language processing in the United Kingdom from 2007 to 2022
Mapping multimorbidity in individuals with schizophrenia and bipolar disorders: evidence from the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLAM BRC) case register
Text mining occupations from the mental health electronic health record: a natural language processing approach using records from the Clinical Record Interactive Search (CRIS) platform in south London, UK
Generation and evaluation of artificial mental health records for Natural Language Processing
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Using natural language processing to extract structured epilepsy data from unstructured clinic letters: development and validation of the ExECT (extraction of epilepsy clinical text) system
Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances
SemEHR: A general-purpose semantic search system to surface semantic data from clinical notes for tailored care, trial recruitment, and clinical research*
CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital
Negative symptoms in schizophrenia: a study in a large clinical sample of patients using a novel automated method
Extracting antipsychotic polypharmacy data from electronic health records: developing and evaluating a novel process
Development and evaluation of a de-identification procedure for a case register sourced from mental health electronic records
Using Prior Information from the Medical Literature in GWAS of Oral Cancer Identifies Novel Susceptibility Variant on Chromosome 4 - the AdAPT Method