Predictive Model of Lyme Disease Epidemic Process Using Machine Learning Approach

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dc.contributor.authorChumachenko, Dmytro
dc.contributor.authorPiletskiy, Pavlo
dc.contributor.authorSukhorukova, Marya
dc.contributor.authorChumachenko, Tetyana
dc.date.accessioned2022-05-02T17:14:04Z
dc.date.available2022-05-02T17:14:04Z
dc.date.issued2022-04-23
dc.identifier.citationPredictive Model of Lyme Disease Epidemic Process Using Machine Learning Approach / D. Chumachenko, P. Piletskiy, M. Sukhorukova, T. Chumachenko // Applied Sciences. – 2022. – Vol. 12. – P. 4282. – DOI: https://doi.org/10.3390/ app12094282.en_US
dc.identifier.urihttps://repo.knmu.edu.ua/handle/123456789/30608
dc.language.isoenen_US
dc.publisherMDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliationsen_US
dc.subjectepidemic processen_US
dc.subjectLyme diseaseen_US
dc.subjectmachine learningen_US
dc.titlePredictive Model of Lyme Disease Epidemic Process Using Machine Learning Approachen_US
dc.typeArticleen_US

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