Lupus, often detected as a chronic disease, is beyond any measure of cure. ANN (Artificial Neural Network) is used to suspect lupus disease in this research paper. If treated in an early stage, this disease can be controlled. Early diagnosis of lupus is required to treat it properly. It is very difficult to diagnose lupus manually by observing various symptoms. An approach is given to diagnose lupus in an efficient way with the help of ANN. An ANN has been designed here to suspect lupus based on laboratory test reports. Lupus is a chronic disease. The ANN consists of many neurons associated with weights. Each test report is dependent on the existence of each neuron. The present paper aimed at designing an Artificial Neural Network model to diagnose the stage of Lupus. Here the data has been collected from North Bengal Medical College for training the network. The proposed ANN used here is a supervised type, where different patterns represent different status of patient.

SLE, Hematocrit, WBC, SLT

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