Integrating remote sensing, GIS, and machine learning for zoonotic cutaneous leishmaniasis modelling

Integrating remote sensing, GIS, and machine learning for zoonotic cutaneous leishmaniasis modelling

Zoonotic Cutaneous Leishmaniasis (ZCL) is a vector-borne disease (VBD) characterized by distinct spatiotemporal patterns. Accurate evaluation of ZCL risk patterns necessitates the utilization of comprehensive epidemiological and ecological data. This study proposes a hybrid model that integrates the...

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Bibliographic Details
Main Authors: Fatemeh Parto Dezfooli, Mohammad Javad Valadan Zoej, Fahimeh Youssefi, Ebrahim Ghaderpour
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Environmental Research Communications
Subjects:
Zoonotic Cutaneous Leishmaniasis (ZCL)
Random Forest (RF)
Extreme Gradient Boosting (XGBoost)
Geographic Information System (GIS)
Remote Sensing (RS)
Artificial Intelligence (AI)
Online Access:https://doi.org/10.1088/2515-7620/adfbbe
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https://doi.org/10.1088/2515-7620/adfbbe

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