Enhancing COVID-19 forecasting precision through the integration of compartmental models, machine learning and variants
Crossref DOI link: https://doi.org/10.1038/s41598-024-69660-5
Published Online: 2024-08-19
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Baccega, Daniele
Castagno, Paolo
Fernández Anta, Antonio
Sereno, Matteo
Text and Data Mining valid from 2024-08-19
Version of Record valid from 2024-08-19
Article History
Received: 20 March 2024
Accepted: 7 August 2024
First Online: 19 August 2024
Competing interests
: The authors declare no competing interests.