Severity Prediction of Poliomyelitis Using Mathematical Model

The major challenge in severity detection of poliomyelitis is its stealthy nature. Hence in this research work Mathematical models have been developed to predict severity of poliomyelitis. presents a comparison of Mathematical models for Severity Prediction of Poliomyelitis. Three Mathematical models were developed viz. Ordinary Differential Equations (ODE), Partial Differential Equations (PDE), and Agent-Based Models (ABM) by using MATLAB IDE. These models show the disease progression in the body from different points of view. These models give a severity score from 0 to 5. It uses patient age and symptoms like fever temperature, muscle strength, reflex score, and breathing condition as input. We trained these mathematical models using records of 1,500 patient, it shows 92% average in predicting the severity level of Poliomyelitis. It supports the doctors to check the severity-level of Poliomyelitis.

Poliomyelitis, Mathematical Modeling, MATLAB, ODE, PDE, ABM

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