Date of Publication :22nd February 2018
Abstract: With big data development in biomedical and medical industries, accurate examination of medical data benefits early disease discovery, patient care and group administrations. In any case, the examination accuracy is lessened when the nature of therapeutic information is deficient. Medical imaging plays a vital role in diagnostic healthcare and deals with a high volume of data collection and processing. In this paper, we streamline machine learning algorithms for classification and prediction of chronic disease outbreak in disease-frequent groups. Deep Learning has emerged as another era in machine learning and is applied to various image processing applications. The fundamental motivation behind the work exhibited in this paper is to apply the idea of Deep Learning algorithms to be specific, Convolutional neural networks (CNN) in image classification. This paper presents the classification of images using deep learning algorithms through spark. Classified different types of skin cancers using Convolutional neural networks in distributed environment achieved in less time with more accuracy
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