4 papers
Clinical-R1: Empowering Large Language Models for Faithful and Comprehensive Reasoning with Clinical Objective Relative Policy Optimization
Boyang Gu, Hongjian Zhou, Bradley Max Segal +6
Recent advances in large language models (LLMs) have shown strong reasoning capabilities through large-scale pretraining and post-training reinforcement learning, demonstrated by D…
Improving Clinical Dataset Condensation with Mode Connectivity-based Trajectory Surrogates
Pafue Christy Nganjimi, Andrew Soltan, Danielle Belgrave +3
Dataset condensation (DC) enables the creation of compact, privacy-preserving synthetic datasets that can match the utility of real patient records, supporting democratised access…
Sensing Cardiac Health Across Scenarios and Devices: A Multi-Modal Foundation Model Pretrained on Heterogeneous Data from 1.7 Million Individuals
Xiao Gu, Wei Tang, Jinpei Han +10
Cardiac biosignals, such as electrocardiograms (ECG) and photoplethysmograms (PPG), are of paramount importance for the diagnosis, prevention, and management of cardiovascular dise…
Bridging the Generalisation Gap: Synthetic Data Generation for Multi-Site Clinical Model Validation
Bradley Segal, Joshua Fieggen, David Clifton +1
Ensuring the generalisability of clinical machine learning (ML) models across diverse healthcare settings remains a significant challenge due to variability in patient demographics…