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Prediction and Estimation of Lung Cancer and Authenticating by CNN-ECC Model

Prediction and Estimation of Lung Cancer and Authenticating by CNN-ECC Model

Smitha Sasi, Srividya B. V.
Copyright: © 2021 |Volume: 11 |Issue: 3 |Pages: 24
ISSN: 1947-9344|EISSN: 1947-9352|EISBN13: 9781799861188|DOI: 10.4018/IJOCI.2021070102
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MLA

Sasi, Smitha, and Srividya B. V. "Prediction and Estimation of Lung Cancer and Authenticating by CNN-ECC Model." IJOCI vol.11, no.3 2021: pp.14-37. http://doi.org/10.4018/IJOCI.2021070102

APA

Sasi, S. & Srividya B. V. (2021). Prediction and Estimation of Lung Cancer and Authenticating by CNN-ECC Model. International Journal of Organizational and Collective Intelligence (IJOCI), 11(3), 14-37. http://doi.org/10.4018/IJOCI.2021070102

Chicago

Sasi, Smitha, and Srividya B. V. "Prediction and Estimation of Lung Cancer and Authenticating by CNN-ECC Model," International Journal of Organizational and Collective Intelligence (IJOCI) 11, no.3: 14-37. http://doi.org/10.4018/IJOCI.2021070102

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Abstract

Miscellany of data analysis on the genesis of disease and the outcome of mortality is very crucial to keep track of the death rates induced due to the disease. The primary detection of the presence of viral infections in lungs is one of the major concerns in the health industry in today's scenario. These infections can lead to mortality. Therefore, the classification and analysis of disease are very pivotal along with security of data. Hence, it is essential for detecting diseases using CNN algorithm at an early stage and generation of medical report automatically. The method is tested for different modals with various lung infections like pneumonia, COVID-19, and cancerous growth in lungs. For these system-generated reports, encryption using ECC algorithm is used to prevent the breach of information while being exchanged from hospital to other organizations or vice versa.

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