Temporal phenotyping and prognostic stratification of patients with sepsis through longitudinal clustering - Ribino, Patrizia; Mannone, Maria; Di Napoli, Claudia; Paragliola, Giovanni; Chicco, Davide; Gasparini, Francesca (BioData mining, 2025)
Keywords: Advances in Data Mining for Biomedical Informatics and Healthcare; Algorithms; Analysis; Bioinformatics; Biomedical and Life Sciences; Care and treatment; Chronic illnesses; Cluster analysis; Clustering; Complexity; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Data Mining and Knowledge Discovery; Datasets; Demographics; Development and progression; Disease; Electronic health records; Electronic medical records; Heart; Heterogeneity; Infection; Infections; Kidneys; Learning strategies; Life Sciences; Longitudinal clustering; Longitudinal studies; Machine learning; Mathematical analysis; Medical prognosis; Medical records; Mortality; Patient trajectories; Patients; Phenotypes; Phenotypic variations; Phenotyping; Physiology; Planning; Prothrombin; Sepsis; Subgroups; Thrombin; Unsupervised machine learning; Urogenital system; Variables; Patient trajectories; Unsupervised machine learning; Longitudinal clustering; Sepsis; Clustering; Electronic health records; Intensive care unit