Severity Prediction of Poliomyelitis Using Mathematical Model
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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.
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