期刊名称：The International Arab Journal of Information Technology
印刷版ISSN：1683-3198
出版年度：2021
卷号：18
期号：6
DOI：10.34028/iajit/18/6/5
语种：English
出版社：Zarqa Private University
摘要：Health informatics has gained a greater focus as the data analytics role has become vital for the last two decades. Many machine learning-based models have evolved to process the huge data involved in this sector. Deep Learning (DL) augmented with Non-Linear Cellular Automata (NLCA) is becoming a powerful tool with great potential to process big data. This will help to develop a system that facilitates parallelization, rapid data storage, and computational power with improved security parameters. This paper provides a novel and robust mechanism with deep learning augmented with non-linear cellular automata with greater security, adaptability for health informatics. The proposed mechanism is adaptable and can address many open problems in medical informatics, bioinformatics, and medical imaging. The security parameters considered in this model are Confidentiality, authorization, and integrity. This method is evaluated for performance, and it reports an average accuracy of 89.32%. The parameters precision, sensitivity, and specificity are considered to measure to measure the accuracy of the model.
