Miss Misaki Seto
Name | Miss Misaki Seto |
---|---|
ORCID | https://orcid.org/0009-0008-9996-0461 |
Email address | u1725457@uel.ac.uk |
Research institute | Health, Sport & Bioscience |
Research outputs
Insights into the contribution of multiple factors on Ixodes ricinus abundance across Europe spanning 20 years using different machine learning algorithms
Lansdell, S., Zorto, A., Seto, M., Negera, E., Sharif, S. and Cutler, S. 2025. Insights into the contribution of multiple factors on Ixodes ricinus abundance across Europe spanning 20 years using different machine learning algorithms. Ticks and Tick-borne Diseases. 16 (1), p. Art. 102437. https://doi.org/10.1016/j.ttbdis.2025.102437Innovative Ensemble Approaches for Assessing Critical Factors for European Tick Abundance
Zorto, A., Lansdell, S., Seto, M., Gobena, E., Cutler, S. and Sharif, S. 2024. Innovative Ensemble Approaches for Assessing Critical Factors for European Tick Abundance. 2024 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies. IEEE. https://doi.org/10.1109/3ict64318.2024.10824268Machine Learning-Based Techniques for Assessing Critical Factors for European Tick Abundance
Zorto, A., Lansdell, S., Seto, M., Negera, E., Sharif, S. and Cutler, S. 2025. Machine Learning-Based Techniques for Assessing Critical Factors for European Tick Abundance. International Journal of Computer Theory and Engineering. 17 (1), pp. 13-20.618
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