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Analyzing trajectories of clinical markers in patients with sepsis through multivariate longitudinal clustering
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CEUR Workshop Proceedings 2024 Scopus收录 摘要：Sepsis is a life-threatening condition with complex and dynamic progression, often requiring timely and personalized treatment strategies. In this paper, we propose a multivariate longitudinal clustering, an advanced data analysis technique, as a powerful approach to understanding the diverse trajectories of sepsis by grouping patients based on multiple clinical variables measured over time. Dynamic Time Warping (DTW) is integrated into the longitudinal clustering as a distance measure to identify subgroups of patients with similar temporal patterns in multivariate data. By leveraging sepsis-related electronic health records (EHRs), which provide rich time-series data on laboratory results along with patient demographics and underlying health conditions, the proposed method reveals distinc |
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(2025-6-4)
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