Unsupervized clustering reveals a tri-phenotype model of hospitalized COVID-19 patients: Beirut cohort study and literature synthesis
Mixed-data clustering revealed three COVID-19 patient clusters indicating the clinical meaningfulness and global reproducibility with prognostic and therapeutic implications. This unsupervised approach may inform early triage and resource allocation. Further prospective validation in diverse, vaccinated populations is warranted.
Authors
- Christopher El Hadi (ORCID: https://orcid.org/0000-0003-4167-4944)
- G. Maalouly (ORCID: https://orcid.org/0000-0003-3677-4609)
- Moussa Riachy (ORCID: https://orcid.org/0000-0003-2146-6945)
- Rindala Saliba (ORCID: https://orcid.org/0000-0002-5635-0945)
- Ghassan Sleilaty
Institutions
- Saint Joseph University (LB)
- Hôtel-Dieu de France (LB)
- Lebanese American University (LB)
Publication Details
- Journal
- Digital Health
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1177/20552076251394299
- Primary Topic
- COVID-19 Clinical Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00