Semi-Supervised KPCA-Based Monitoring Techniques for Detecting COVID-19 Infection through Blood Tests

This study introduces a new method for identifying COVID-19 infections using blood test data as part of an anomaly detection problem by combining the kernel principal component analysis (KPCA) and one-class support vector machine (OCSVM). This approach aims to differentiate healthy individuals from...

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Detalles Bibliográficos
Autores principales: Harrou, Fouzi, Dairi, Abdelkader, Dorbane, Abdelhakim, Kadri, Farid, Sun, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10138088/
https://www.ncbi.nlm.nih.gov/pubmed/37189568
http://dx.doi.org/10.3390/diagnostics13081466

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10138088/
https://www.ncbi.nlm.nih.gov/pubmed/37189568
http://dx.doi.org/10.3390/diagnostics13081466

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