Automated Detection and Classifying Diabetes Mellitus using CNN

Machine learning algorithms have recently attracted more attention in the medical field and have been successfully used in a variety of medical applications. Machine learning is used to assist medical practitioners to solve complicated problems. Thus to function autonomously without seeking any assistance or help from a person, a well-known branch of machine learning called deep learning completes several related tasks parallely. It is successfully used in a variety of applications, including disease prediction and disease progression. Since tasks are assumed to be related to one another, existing learning methods adapts the Convolution neural network (CNN) to classify the diabetes mellitus disease effectively. To detect the abnormality, the proposed work uses a deep learning network that includes a novel CNN model that splits the data into separate training and testing sets before doing classification. Using CNN, the proposed work achieves better accuracy and outperforms well to the best of our knowledge.