Zika Virus Prediction Using AI-Driven Technology and Hybrid Optimization Algorithm in Healthcare.

Pankaj Dadheech,Shivam Tiwari,Sweta Gupta,Sarvesh Kumar,Abolfazl Mehbodniya,Henry Kwame Atiglah,Pooja Singh,Xingwang Li

doi:10.1155/2022/2793850

Abstract

The Zika virus presents an extraordinary public health hazard after spreading from Brazil to the Americas. In the absence of credible forecasts of the outbreak's geographic scope and infection frequency, international public health agencies were unable to plan and allocate surveillance resources efficiently. An RNA test will be done on the subjects if they are found to be infected with Zika virus. By training the specified characteristics, the suggested Hybrid Optimization Algorithm such as multilayer perceptron with probabilistic optimization strategy gives forth a greater accuracy rate. The MATLAB program incorporates numerous machine learning algorithms and artificial intelligence methodologies. It reduces forecast time while retaining excellent accuracy. The projected classes are encrypted and sent to patients. The Advanced Encryption Standard (AES) and TRIPLE Data Encryption Standard (TEDS) are combined to make this possible (DES). The experimental outcomes improve the accuracy of patient results communication. Cryptosystem processing acquires minimal timing of 0.15 s with 91.25 percent accuracy.

Highlights

An infection’s prelude and rapid spread to other regions of the globe attract the attention of the international community
Even males who are infected with the 20 viruses may spread the virus to their sexual partners via anal, oral, or Journal of Healthcare Engineering vaginal intercourse. e increasing population in urban areas has increased the demand for water portability, which has resulted in people storing water in their homes, causing the Aedes aegypti mosquitoes to breed quickly in that climatic condition [2]. e increasing population in urban areas has increased the demand for water portability, which has resulted in people storing water in their homes
We were unable to get real-time data because we needed to protect the anonymity of the patients who had been afflicted with the Zika virus; we developed synthetic data

Summary

Introduction

An infection’s prelude and rapid spread to other regions of the globe attract the attention of the international community. E increasing population in urban areas has increased the demand for water portability, which has resulted in people storing water in their homes, causing the Aedes aegypti mosquitoes to breed quickly in that climatic condition [2]. If a user wants to make use of the advantages of cloud computing, he or she must first choose an appropriate network and make use of the dispersed resources and arrangements made possible by cloud computing When it comes to data transfer, the protection of the information is critical [4]. Zika virus illness prediction and data security are critical for both sender. E use of encryption methods such as symmetric and asymmetric cryptography is investigated for the purpose of data security. The suggested Hybrid Encryption technique is used for the purpose of safeguarding the data in the shortest amount of time possible, resulting in improved performance. The suggested Hybrid Encryption technique is used for the purpose of safeguarding the data in the shortest amount of time possible, resulting in improved performance. e paper has the following structure: Section 2 consists of literature survey, Section 3 consists of methodology and outcome of proposed algorithm, and Section 5 consists of conclusions with future work

Literature Survey

Proposed Zika Virus Prediction Using MLP Classifier

Experimental Results

Conclusion