Identifying Subgroups of ICU Patients Using End-to-End Multivariate Time-Series Clustering Algorithm Based on Real-World Vital Signs Data

no code implementations • 3 Jun 2023 • Tongyue Shi, Zhilong Zhang, Wentie Liu, Junhua Fang, Jianguo Hao, Shuai Jin, Huiying Zhao, Guilan Kong

This study employed the MIMIC-IV database as data source to investigate the use of dynamic, high-frequency, multivariate time-series vital signs data, including temperature, heart rate, mean blood pressure, respiratory rate, and SpO2, monitored first 8 hours data in the ICU stay.

Clustering ICU Mortality +3