An Intelligent Healthcare Cyber Physical Framework for Encephalitis Diagnosis Based on Information Fusion and Soft-Computing Techniques

Abstract

Viral encephalitis is a contagious disease that causes life insecurity and is considered one of the major health concerns worldwide. It causes inflammation of the brain and, if left untreated, can have persistent effects on the central nervous system. Conspicuously, this paper proposes an intelligent cyber-physical healthcare framework based on the IoT-fog-cloud collaborative network, employing soft-computing technology and information fusion. The proposed framework uses IoT-based sensors, electronic medical records, and user devices for data acquisition. The fog layer, composed of numerous nodes, processes the most specific encephalitis symptomrelated data to classify possible encephalitis cases in real time to issue an alarm when a significant health emergency occurs. Furthermore, the cloud layer involves a multi-step data processing scheme for in-depth data analysis. First, data obtained across multiple data generation sources are fused to obtain a more consistent, accurate, and reliable feature set. Data preprocessing and feature selection techniques are applied to the fused data for dimensionality reduction over the cloud computing platform. An adaptive neuro-fuzzy inference system is applied in the cloud to determine the risk of a disease and classify the results into one of four categories: no risk, probable risk, low risk, and acute risk. Moreover, the alerts are generated and sent to the stakeholders based on the risk factor. Finally, the computed results are stored in the cloud database for future use. For validation purposes, various experiments are performed using real-time datasets. The analysis results performed on the fog and cloud layers show higher performance than the existing models. Future research will focus on the resource allocation in the cloud layer while considering various security aspects to improve the utility of the proposed work.

Artificial Intelligence in Global Epidemics, Part 2

“…Ideas in the context of COVID-19 are nowadays widespread targeting mobility aspects [ 2 , 9 ], evaluation of information relevance [ 12 ], introducing advanced intelligent cyber-physical healthcare framework [ 6 ] and forecasting COVID-19 reliability of the countries [ 4 ].…”

“…Hence, this special issue has been divided into two parts, where Part 1 was already published in 2021 [ 7 ]. Part 2 with 13 articles [ 1 – 6 , 8 – 14 ] is introduced in this editorial. Later publications about COVID-19 will be included in the regular issues of the New Generation Computing journal.…”

Blockchain-enabled healthcare monitoring system for early Monkeypox detection

“…Owing to the emergence of such pandemics, the number of patients is significantly rising, thereby making patients’ health record management a challenging task. Electronic health records (EHR) transform traditional health management tasks in a multitude of ways [ 8 ]. EHR keeps medical records in a digital format that is in line with the care and can be instantaneously accessed and securely disseminated across various entities.…”

Evaluation of soft computing in methodology for calculating information protection from parameters of its distribution in social networks

“…There are four parts to the user data that must be protected: i) data on usage; information gathered from computers, including sensitive data; information regarding a bank account, health, etc. iii) Information that identifies an individual; information that could be used to find person (iv) distinct device identities; information that could be traced in a single way, such as unique hardware identities or IP addresses [3]. Computational resources like CPU, memory, disk, and communication bandwidth are made possible by virtualization technology in the cloud.…”