36 citations · 101 across the 13 of their papers we have counts for
14 papers
An Echo Chamber of One: Should AI Psychosis Be a Distinct Clinical Entity?
Joshua Au Yeung, Hamilton Morrin, Vincent Ng +2
"AI psychosis" has entered public and clinical discourse as a label for the onset or exacerbation of psychotic symptoms, most commonly delusions, following intensive interaction wi…
Foresight-England: Development of a National-Scale Generative AI Model of Electronic Health Records for Medical Event Prediction across the COVID-19 Pandemic
Simon Ellershaw, Christopher Tomlinson, Zeljko Kraljevic +6
Foresight-England (Foresight-E) is the first national-scale generative foundation model of electronic health records (EHRs), developed as a research pilot strictly for COVID-19 res…
The Psychogenic Machine: Simulating AI Psychosis, Delusion Reinforcement and Harm Enablement in Large Language Models
Joshua Au Yeung, Jacopo Dalmasso, Luca Foschini +2
Background: Emerging reports of "AI psychosis" are on the rise, where user-LLM interactions may exacerbate or induce psychosis or adverse psychological symptoms. Whilst the sycopha…
Large Language Models for Medical Forecasting -- Foresight 2
Zeljko Kraljevic, Joshua Au Yeung, Daniel Bean +2
Foresight 2 (FS2) is a large language model fine-tuned on hospital data for modelling patient timelines (GitHub 'removed for anon'). It can understand patients' clinical notes and…
Validating transformers for redaction of text from electronic health records in real-world healthcare
Zeljko Kraljevic, Anthony Shek, Joshua Au Yeung +8
Protecting patient privacy in healthcare records is a top priority, and redaction is a commonly used method for obscuring directly identifiable information in text. Rule-based meth…
Challenges and Opportunities of Using Transformer-Based Multi-Task Learning in NLP Through ML Lifecycle: A Survey
Lovre Torbarina, Tin Ferkovic, Lukasz Roguski +3
The increasing adoption of natural language processing (NLP) models across industries has led to practitioners' need for machine learning systems to handle these models efficiently…
Foresight -- Generative Pretrained Transformer (GPT) for Modelling of Patient Timelines using EHRs
Zeljko Kraljevic, Dan Bean, Anthony Shek +9
Background: Electronic Health Records hold detailed longitudinal information about each patient's health status and general clinical history, a large portion of which is stored wit…
MedGPT: Medical Concept Prediction from Clinical Narratives
Zeljko Kraljevic, Anthony Shek, Daniel Bean +3
The data available in Electronic Health Records (EHRs) provides the opportunity to transform care, and the best way to provide better care for one patient is through learning from…
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…
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…
MedCAT -- Medical Concept Annotation Tool
Zeljko Kraljevic, Daniel Bean, Aurelie Mascio +5
Biomedical documents such as Electronic Health Records (EHRs) contain a large amount of information in an unstructured format. The data in EHRs is a hugely valuable resource docume…
MedCATTrainer: A Biomedical Free Text Annotation Interface with Active Learning and Research Use Case Specific Customisation
Thomas Searle, Zeljko Kraljevic, Rebecca Bendayan +2
We present MedCATTrainer an interface for building, improving and customising a given Named Entity Recognition and Linking (NER+L) model for biomedical domain text. NER+L is often…