AI Medical Diagnosis Application

Artificial Intelligence aims to mimic the human cognitive powers. AI is also into healthcare where it's been used for automating the diagnosis processes powered by increased availability of healthcare data. This research work develops an application, which can be used in diagnostic centers for multiple diseases diagnosis like Arrhythmia classification using ECG Image analysis, Malaria using Cell images, Brain tumor detection using MRI Scans and many more. At Present, this research work attempts to develop an Arrhythmia classification using ECG Image analysis and would add other diagnosis later on. Basically, ECG signals are used for analysis of Arrhythmia. The irregularities of heart beat are commonly called Arrhythmia. Here, a Convolutional Neural Network model is proposed for the classification of signals from ECG images to different classes. There are many different classes which are normal beat, Premature ventricular contraction beat, paced beat, atrial bundle branch block beat, left bundle branch block beat, atrial premature contraction beat, ventricular flutter wave beat, and ventricular escape beat, etc.