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@article{154188,
        author = {Johncy G},
        title = {SECURE DATA TRANSMISSION AND RISK PREDICTION IN SIMILAR DISEASES USING CONVOLUTIONAL NEURAL NETWORK  },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {7},
        pages = {78-85},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=154188},
        abstract = {Medical facilities need to be advanced so that better decisions for patient diagnosis and treatment options can be made. Deep learning in healthcare aids the humans to process huge and complex medical datasets and then analyze them into clinical insights. This then can further be used by physicians in providing medical care. Hence deep learning when implemented in healthcare can leads to increased patient satisfaction. In this work, we try to implement functionalities of deep learning in healthcare in a single system. Instead of diagnosis, when a disease prediction is implemented using certain deep learning predictive algorithms then healthcare can be made smart. Some cases can occur when early diagnosis of a disease is not within reach. Hence disease prediction can be effectively implemented. The encrypted health report is uploaded to the cloud server and  medical data Provider get the patient report from the cloud server decrypt report by using RSA with DSA key. Then apply Convolutional Neural Network  algorithm to find the disease caused by patient based on the symptoms and also find the level of risk of diseases in three stages namely low, medium, high.},
        keywords = {Deep learning, Disease prediction, CNN, RSA, DSA.},
        month = {},
        }