Alghamdi Ahmed Mohammed, Al Shehri Waleed A, Almalki Jameel, Jannah Najlaa, Alsubaei Faisal S
Department of Software Engineering, College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia.
Department of Computing, College of Engineering and Computing in Al-Lith, Umm Al-Qura University, Makkah, Saudi Arabia.
PLoS One. 2024 Aug 1;19(8):e0305483. doi: 10.1371/journal.pone.0305483. eCollection 2024.
The COVID-19 epidemic is affecting individuals in many ways and continues to spread all over the world. Vaccines and traditional medical techniques are still being researched. In diagnosis and therapy, biological and digital technology is used to overcome the fear of this disease. Despite recovery in many patients, COVID-19 does not have a definite cure or a vaccine that provides permanent protection for a large number of people. Current methods focus on prevention, monitoring, and management of the spread of the disease. As a result, new technologies for combating COVID-19 are being developed. Though unreliable due to a lack of sufficient COVID-19 datasets, inconsistencies in the datasets availability, non-aggregation of the database because of conflicting data formats, incomplete information, and distortion, they are a step in the right direction. Furthermore, the privacy and confidentiality of people's medical data are only partially ensured. As a result, this research study proposes a novel, cooperative approach that combines big data analytics with relevant Artificial Intelligence (AI) techniques and blockchain to create a system for analyzing and detecting COVID-19 instances. Based on these technologies, the reliability, affordability, and prominence of dealing with the above problems required time. The architecture of the proposed model will analyze different data sources for preliminary diagnosis, detect the affected area, and localize the abnormalities. Furthermore, the blockchain approach supports the decentralization of the central repository so that it is accessible to every stakeholder. The model proposed in this study describes the four-layered architecture. The purpose of the proposed architecture is to utilize the latest technologies to provide a reliable solution during the pandemic; the proposed architecture was sufficient to cover all the current issues, including data security. The layers are unique and individually responsible for handling steps required for data acquisition, storage, analysis, and reporting using blockchain principles in a decentralized P2P network. A systematic review of the technologies to use in the pandemic covers all possible solutions that can cover the issue best and provide a secure solution to the pandemic.
新冠疫情正以多种方式影响着个人,且仍在全球范围内持续蔓延。疫苗和传统医学技术仍在研究之中。在诊断和治疗方面,生物和数字技术被用于克服对这种疾病的恐惧。尽管许多患者康复了,但新冠病毒没有明确的治愈方法或能为大量人群提供永久保护的疫苗。当前的方法侧重于疾病传播的预防、监测和管理。因此,对抗新冠病毒的新技术正在被研发。尽管由于缺乏足够的新冠病毒数据集、数据集可用性不一致、数据格式冲突导致数据库无法聚合、信息不完整以及数据失真等原因而不可靠,但它们是朝着正确方向迈出的一步。此外,人们医疗数据的隐私和保密性仅得到部分保障。因此,本研究提出一种新颖的协作方法,将大数据分析与相关人工智能(AI)技术及区块链相结合,创建一个用于分析和检测新冠病毒病例的系统。基于这些技术,解决上述问题所需的可靠性、可承受性和卓越性尚需时日。所提出模型的架构将分析不同数据源以进行初步诊断,检测受影响区域,并定位异常情况。此外,区块链方法支持中央存储库的去中心化,以便每个利益相关者都能访问。本研究中提出的模型描述了四层架构。所提出架构的目的是利用最新技术在疫情期间提供可靠的解决方案;所提出的架构足以涵盖所有当前问题,包括数据安全。这些层是独特的,各自负责在去中心化的对等网络中使用区块链原则处理数据采集、存储、分析和报告所需的步骤。对疫情期间所使用技术的系统综述涵盖了所有可能的最佳解决方案,这些方案能够涵盖该问题并为疫情提供安全的解决方案。