Genetic Algorithms for Feature Selection in the Classification of COVID-19 Patients
The study's results highlight the ability to use HRV parameters extraction from PPG signals, combined with genetic algorithms and machine learning classifiers, to determine which features are most helpful in discriminating between healthy and mild-severity COVID-19-affected subjects.
Authors
- Leonardo Bocchi (ORCID: https://orcid.org/0000-0001-5109-3399)
- Mateusz Soliński (ORCID: https://orcid.org/0000-0002-6461-1738)
- E. Rossi (ORCID: https://orcid.org/0000-0002-1020-829X)
- Piergiorgio Francia (ORCID: https://orcid.org/0000-0001-5176-1449)
- Antonio Lanatà (ORCID: https://orcid.org/0000-0002-6540-5952)
- Teodor Buchner (ORCID: https://orcid.org/0000-0003-0030-3194)
- Cosimo Aliani (ORCID: https://orcid.org/0000-0002-2023-3464)
Institutions
- Warsaw University of Technology (PL)
- King's College London (GB)
- University of Florence (IT)
Publication Details
- Journal
- Bioengineering
- Published
- 2024-09-23
- DOI
- https://doi.org/10.3390/bioengineering11090952
- Citations
- 4
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 1.62
Funders
- Regione Toscana