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Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45614, first published .
Representation Learning and Spectral Clustering for the Development and External Validation of Dynamic Sepsis Phenotypes: Observational Cohort Study

Representation Learning and Spectral Clustering for the Development and External Validation of Dynamic Sepsis Phenotypes: Observational Cohort Study

Representation Learning and Spectral Clustering for the Development and External Validation of Dynamic Sepsis Phenotypes: Observational Cohort Study

Journals

  1. Tekin A, Mosolygó B, Huo N, Xiao G, Lal A. Bundle compliance patterns in septic shock and their association with patient outcomes: an unsupervised cluster analysis. Internal and Emergency Medicine 2025;20(2):489 View
  2. Wang R, Xu J, He M. Blood leukocyte-based clusters in patients with traumatic brain injury. Frontiers in Immunology 2025;15 View
  3. Ter Horst S, ter Maaten J, van Meurs M, Moser J, Bouma H. Why Has Biomarker-Guided Fluid Resuscitation for Sepsis Not Been Implemented in Clinical Practice?. Critical Care Explorations 2025;7(6):e1274 View
  4. . Role of artificial intelligence as adjuvant therapy for sepsis fluid resuscitation. New Medicine 2025:1 View
  5. Papareddy P, Lobo T, Holub M, Bouma H, Maca J, Strodthoff N, Herwald H. Transforming sepsis management: AI-driven innovations in early detection and tailored therapies. Critical Care 2025;29(1) View
  6. Wiedermann C, Zaboli A, Turcato G. Early Vasoplegia and Endothelial Protection in Sepsis: A Physiology-Guided Framework for Timely Albumin and Norepinephrine Therapy. International Journal of Translational Medicine 2025;6(1):2 View
  7. Kyriazopoulou E, Karakike E, Myrianthefs P. Artificial Intelligence- and Machine Learning-Assisted Subphenotyping for Personalized Immunotherapy in Sepsis. Journal of Personalized Medicine 2026;16(1):28 View
  8. Ford J, Boussina A, Malhotra A, Wardi G, Nemati S. Dynamic sepsis endotypes: instability or expected signal of biological progression?. Intensive Care Medicine 2026;52(3):613 View
  9. Buican I, Buican-Chirea A, Radulescu D, Udristoiu I, Gheorman V, Cojocaru D, Streba C. Integrated Pulmonary Severity Score (IPSS) for COPD: A Psycho-Respiratory Risk Index Supported by Explainable Machine Learning. Diagnostics 2026;16(4):507 View
  10. Rademaker E, de Grooth H, Cremer O. Dynamic sepsis endotypes: instability or expected signal of biological progression? Author's reply. Intensive Care Medicine 2026;52(3):615 View
  11. Jeong D, Park J, Maeng S, Choi J, Lee G, Hwang S, Kim C, Park J, Shin T. Artificial intelligence-driven cluster analysis for identifying clinical phenotypes in suspected sepsis patients in the emergency department. BMC Emergency Medicine 2026 View
  12. Yang M, Shi N, Chen H, Po E, Ng P, Lai P, Wu Y, Fong D. Multimodal Artificial Intelligence for Precision Critical Care: A Scoping Review. Health Data Science 2026;6 View