Author

Micanaldo Ernesto Francisco

Institutions: Lúrio University, Ehime University, Center for Marine Environmental Studies, Ehime University

Observed institutions: Lúrio University, Ehime University, Center for Marine Environmental Studies, Ehime University

ORCID: 0000-0002-3337-7432

Observed ORCID: 0000-0002-3337-7432

OpenAlex ID: A5062610579

Dengue disease dynamics are modulated by the combined influences of precipitation and landscape: A machine learning approach

2021 · Micanaldo Ernesto Francisco, Thaddeus M. Carvajal, et al. · The Science of The Total Environment · 52

An Integrated mHealth App for Dengue Reporting and Mapping, Health Communication, and Behavior Modification: Development and Assessment of Mozzify

2019 · Von Ralph Dane Marquez Herbuela, Tomonori Karita, et al. · JMIR Formative Research · 36

Hybrid Machine Learning Approach to Zero-Inflated Data Improves Accuracy of Dengue Prediction

2024 · Micanaldo Ernesto Francisco, Thaddeus M. Carvajal, et al. · PLoS neglected tropical diseases · 22

A review on modulation of gut microbiome interaction for the management of shrimp aquaculture and proposal of the introduction of deep learning-based approach for shrimp disease detection

2025 · Md. Zakaria, Micanaldo Ernesto Francisco, et al. · The Microbe · 15

Innovative house structures for malaria vector control in Nampula district, Mozambique: assessing mosquito entry prevention, indoor comfort, and community acceptance

2024 · Micanaldo Ernesto Francisco, Kozo Watanabe · Frontiers in Public Health · 12

Bridging technology and epidemiology: artificial intelligence-driven innovations in mosquito and mosquito-borne disease research

2026 · Paolo Ramon D. C. Pacheco, Abigaile Mia J. Hila, et al. · BMC Artificial Intelligence

Deep learning identifies water bodies from low-cost drone images for mosquito larval habitat mapping

2026 · Micanaldo Ernesto Francisco, Andri Ruliansyah, et al. · Scientific Reports

Works count: 7

Citation count: 137

H-index: 5

I10-index: 5