4 citations · 4 across the 4 of their papers we have counts for
5 papers
PRISM-CTG: A Foundation Model for Cardiotocography Analysis with Multi-View SSL
Sheng Wong, Ravi Shankar, Beth Albert +5
Supervised deep learning models for automated CTG analysis are typically constrained by narrowly curated labelled datasets and limited patient cohorts, leaving substantial volumes…
CleanCTG: A Deep Learning Model for Multi-Artefact Detection and Reconstruction in Cardiotocography
Sheng Wong, Beth Albert, Gabriel Davis Jones
Cardiotocography (CTG) is essential for fetal monitoring but is frequently compromised by diverse artefacts which obscure true fetal heart rate (FHR) patterns and can lead to misdi…
Reducing Large Language Model Safety Risks in Women's Health using Semantic Entropy
Jahan C. Penny-Dimri, Magdalena Bachmann, William R. Cooke +7
Large language models (LLMs) hold substantial promise for clinical decision support. However, their widespread adoption in medicine, particularly in healthcare, is hindered by thei…
PatchCTG: Patch Cardiotocography Transformer for Antepartum Fetal Health Monitoring
M. Jaleed Khan, Manu Vatish, Gabriel Davis Jones
Antepartum Cardiotocography (CTG) is vital for fetal health monitoring, but traditional methods like the Dawes-Redman system are often limited by high inter-observer variability, l…
The OxMat dataset: a multimodal resource for the development of AI-driven technologies in maternal and newborn child health
M. Jaleed Khan, Ioana Duta, Beth Albert +3
The rapid advancement of Artificial Intelligence (AI) in healthcare presents a unique opportunity for advancements in obstetric care, particularly through the analysis of cardiotoc…