Collaborative learning of common latent representations in routinely collected multivariate ICU physiological signals

arXiv:2402.17917v1 Announce Type: new
Abstract: In Intensive Care Units (ICU), the abundance of multivariate time series presents an opportunity for machine learning (ML) to enhance patient phenotyping. In contrast to previous research focused on electronic health records (EHR), here we propose an ML approach for phenotyping using routinely collected physiological time series data. Our new algorithm integrates Long Short-Term Memory (LSTM) networks with collaborative filtering concepts to identify common physiological states across patients. Tested on real-world ICU clinical data for …

abstract arxiv collaborative contrast cs.lg ehr electronic electronic health records health machine machine learning multivariate patient records research series time series type units