5 citations · 6 across the 5 of their papers we have counts for
5 papers
Importance of Prompt Optimisation for Error Detection in Medical Notes Using Language Models
Craig Myles, Patrick Schrempf, David Harris-Birtill
Errors in medical text can cause delays or even result in incorrect treatment for patients. Recently, language models have shown promise in their ability to automatically detect er…
Grounding Chest X-Ray Visual Question Answering with Generated Radiology Reports
Francesco Dalla Serra, Patrick Schrempf, Chaoyang Wang +3
We present a novel approach to Chest X-ray (CXR) Visual Question Answering (VQA), addressing both single-image image-difference questions. Single-image questions focus on abnormali…
The role of noise in denoising models for anomaly detection in medical images
Antanas Kascenas, Pedro Sanchez, Patrick Schrempf +9
Pathological brain lesions exhibit diverse appearance in brain images, in terms of intensity, texture, shape, size, and location. Comprehensive sets of data and annotations are dif…
Paying Per-label Attention for Multi-label Extraction from Radiology Reports
Patrick Schrempf, Hannah Watson, Shadia Mikhael +6
Training medical image analysis models requires large amounts of expertly annotated data which is time-consuming and expensive to obtain. Images are often accompanied by free-text…
Language Transfer for Early Warning of Epidemics from Social Media
Mattias Appelgren, Patrick Schrempf, Matúš Falis +2
Statements on social media can be analysed to identify individuals who are experiencing red flag medical symptoms, allowing early detection of the spread of disease such as influen…