Open AccessDisease Classification with E-Report Generation, Authentication and Encryption
Author(s) -
Ashish Kurane
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.35528
Subject(s) - encryption , anticipation (artificial intelligence) , authentication (law) , computer science , revelation , field (mathematics) , convolutional neural network , computer security , artificial intelligence , mathematics , art , literature , pure mathematics
The assortment of data analysis on the origin of diseases and consequences of mortality is essential to keep track of death rates caused due to diseases. Thus, the classification of diseases is very crucial. Cancer is one of the huge and major diseases of concern in the world. Machine learning is extensively implemented in the medical field in the anticipation of medical errors and early revelation of diseases. Along with the implementation of technology in medical field there is need for authentication to safeguard the privacy rights of patient’s health information. Thus, in this paper, revelation of disease using CNN (Convolutional Neural Networks) algorithm is achieved along with authentication and automatic generation of e-medical report which is further encrypted using RSA (Rivest, Shamir, Adleman) algorithm to overcome the breach of information while being shared from one hospital to another.