AI RESEARCH
PRISM-CTG: A Foundation Model for Cardiotocography Analysis with Multi-View SSL
arXiv CS.LG
•
ArXi:2605.02917v1 Announce Type: new Supervised deep learning models for automated CTG analysis are typically constrained by narrowly curated labelled datasets and limited patient cohorts, leaving substantial volumes of physiologically informative clinical recordings untapped. To address this limitation, we propose Physiology-aware Representation Learning via Integrated Self-supervision and Metadata for CTG (PRISM-CTG), a clinically grounded self-supervised foundation model (FM) for CTG that leverages large-scale unlabelled recordings to learn transferable domain-level representations.