Temporal Design Patterns for Digital Phenotype Cohort Selection in Critical Care: Systematic Literature Assessment and Qualitative Synthesis

Journals

1. Hur B, Verspoor K, Baldwin T, Hardefeldt L, Pfeiffer C, Mansfield C, Scarborough R, Gilkerson J. Using natural language processing and patient journey clustering for temporal phenotyping of antimicrobial therapies for cat bite abscesses. Preventive Veterinary Medicine 2024;223:106112 View
2. da Silva A, Merolli M, Fini N, Granger C, Gustafson O, Parry S. Digital health interventions in adult intensive care and recovery after critical illness to promote survivorship care. Journal of the Intensive Care Society 2025;26(1):96 View
3. Lacey J, Spielfogel E, Benbow J, Savage K, Lin K, Anderson C, Clague-DeHart J, Duffy C, Martinez M, Park H, Thompson C, Wang S, Chandra S, Drif A. Automated self-service cohort selection for large-scale population sciences and observational research: The California teachers study researcher platform. PLOS One 2025;20(5):e0296611 View
4. Senevirathna P, Pires D, Capurro D. Uncovering digital overdiagnosis – Quantification and mitigation using clinical trajectories: Heparin-induced thrombocytopenia use case. Journal of Biomedical Informatics 2025;169:104876 View