Andrade-Girón, Daniel and Carreño-Cisneros, Edgardo and Mejía-Dominguez, Cecilia and Velásquez-Gamarra, Julia and Marín-Rodriguez, William and Villarreal-Torres, Henry and Meleán-Romero, Rosana (2023) Support vector machine with optimized parameters for the classification of patients with COVID-19. EAI Endorsed Transactions on Pervasive Health and Technology.
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Abstract
Introduction. The COVID-19 pandemic has had a significant impact worldwide, especially in health, where it is crucial to identify patients at high risk of clinical deterioration early.
Objective. This study aimed to design a model based on the support vector machine (SVM) algorithm, optimizing its
| Item Type: | Article |
|---|---|
| Date Deposited: | 04 Mar 2026 16:31 |
| Last Modified: | 17 Apr 2026 02:38 |
| URI: | http://eprints.eai.eu/id/eprint/44171 |
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