50 citations · 110 across the 11 of their papers we have counts for
14 papers
A rubric landscape for evaluating clinical reasoning in large language models: what exists, what is missing, and what needs to be combined
Zhangshu Joshua Jiang, Zina Ibrahim, James T. Teo
Exam-style accuracy does not establish whether large language models (LLMs) reason well over clinical records. We define clinical reasoning as integrating and updating evidence acr…
A Proposed Rubric for Evaluating Expressed Clinical Reasoning in Large Language Model Responses
Zhangshu Joshua Jiang, Zina Ibrahim, James T. Teo
We propose a rubric for assessing expressed clinical reasoning in model responses, drawing on three bodies of work: medical education assessment frameworks (ART, SCT, Key Feature P…
Framework to generate perfusion map from CT and CTA images in patients with acute ischemic stroke: A longitudinal and cross-sectional study
Chayanin Tangwiriyasakul, Pedro Borges, Stefano Moriconi +6
Stroke is a leading cause of disability and death. Effective treatment decisions require early and informative vascular imaging. 4D perfusion imaging is ideal but rarely available…
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…
Unsupervised 3D out-of-distribution detection with latent diffusion models
Mark S. Graham, Walter Hugo Lopez Pinaya, Paul Wright +8
Methods for out-of-distribution (OOD) detection that scale to 3D data are crucial components of any real-world clinical deep learning system. Classic denoising diffusion probabilis…
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…
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…
Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models
Walter H. L. Pinaya, Mark S. Graham, Robert Gray +12
Deep generative models have emerged as promising tools for detecting arbitrary anomalies in data, dispensing with the necessity for manual labelling. Recently, autoregressive trans…
Transformer-based out-of-distribution detection for clinically safe segmentation
Mark S Graham, Petru-Daniel Tudosiu, Paul Wright +9
In a clinical setting it is essential that deployed image processing systems are robust to the full range of inputs they might encounter and, in particular, do not make confidently…
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…
Neuradicon: operational representation learning of neuroimaging reports
Henry Watkins, Robert Gray, Adam Julius +10
Radiological reports typically summarize the content and interpretation of imaging studies in unstructured form that precludes quantitative analysis. This limits the monitoring of…
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…