Design of MLP Based Model for Analysis of Patient Suffering from Influenza

Cough is a defensive system of the respiratory track that might be deliberate or reflex. It shows up with normal disease (Cold) leads towards influenza. But when it gets to be chronic it can extremely impair the life. The chronic case might lead towards tuberculosis (TB). To outline a computerized framework for influenza (Cough) detection is key aspect for medical expert and in addition to patients. The advantage could permit the evaluation of pathology in such illnesses. In this paper, authors have taken an endeavour to detect influenza in shrewd way. The model has been composed utilizing cascaded Multi-Layer Perceptron (MLP). The network is trained by LM algorithm. In initial step the symptoms are bolstered to finalize the type of pathological tests. It is encouraged with seven attributes. Once the type of pathological test has been detected, its attributes are nourished to the second stage to choose with respect to influenza or some other because of chronic case. It will help to the physicians to endorse the patients. The MLP based framework performs well as confirmed for such case.