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A novel hybrid model for species distribution prediction of Soil-transmitted helminthiasis (STH) under Soil Temperature Conditions using Random Forest and Particle Swarm Optimization Algorithm

Domaine:

healthcare

Type de record:

paper
Créateur:
TaiJohIBRCal
Éditeur:
Spr
Hôte:
Abstract Soil Transmitted Helminthiases (STH) are one the most common neglected Tropical diseases in Nigeria, primarily transmitted through soil contaminated with human feces, which led to this research of the effect of ecological factors such as soil temperature on the distribution of STH in Nigeria. In this paper, we propose a hybrid model combining the popular species distribution machine learning algorithm Random Forest and Particle Swarm Optimization Algorithm for feature selection, and a comprehensive analysis on the STH dataset. Our model was compared with a deep learning algorithm of Artificial Neural Network, RFPSO with 91.40% accuracy, RF with 87% and ANN with 80.97%.

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