4 papers
Evaluating the Presence of Sex Bias in Clinical Reasoning by Large Language Models
Isabel Tsintsiper, Sheng Wong, Beth Albert +2
Large language models (LLMs) are increasingly embedded in healthcare workflows for documentation, education, and clinical decision support. However, these systems are trained on la…
Large language models surpass domain-specific architectures for antepartum electronic fetal monitoring analysis
Sheng Wong, Ravi Shankar, Beth Albert +1
Foundation models (FMs) and large language models (LLMs) have demonstrated promising generalization across diverse domains for time-series analysis, yet their potential for electro…
Predicting Fetal Outcomes from Cardiotocography Signals Using a Supervised Variational Autoencoder
John Tolladay, Beth Albert, Gabriel Davis Jones
Objective: To develop and interpret a supervised variational autoencoder (VAE) model for classifying cardiotocography (CTG) signals based on pregnancy outcomes, addressing interpre…
Energy Landscapes Enable Reliable Abstention in Retrieval-Augmented Large Language Models for Healthcare
Ravi Shankar, Sheng Wong, Lin Li +4
Reliable abstention is critical for retrieval-augmented generation (RAG) systems, particularly in safety-critical domains such as women's health, where incorrect answers can lead t…