Artificial Neural Network Model in Stroke Diagnosis

We present a model of Artificial Neural Network (ANN) applied to stroke diagnosis. We use input data related to stroke that serves as inputs for the ANN. These data include clinical symptoms together with stroke risk factors. Each type of data provides input that is evaluated and used during the ANN processing. The adaptive learning algorithm can be used with a plethora of types of medical data and integrated into categorized outputs.