利用 CronaSona 构建 AI 医疗保健生态系统框架,用于新冠病毒检测和预测。
An AI healthcare ecosystem framework for Covid-19 detection and forecasting using CronaSona.
机构信息
Information System Department, Faculty of Computers & Information, Suez University, Suez, Egypt.
出版信息
Med Biol Eng Comput. 2024 Jul;62(7):1959-1979. doi: 10.1007/s11517-024-03058-3. Epub 2024 Mar 13.
The primary purpose of this paper is to establish a healthcare ecosystem framework for COVID-19, CronaSona. Unlike some studies that focus solely on detection or forecasting, CronaSona aims to provide a holistic solution, for managing data and/or knowledge, incorporating detection, forecasting, expert advice, treatment recommendations, real-time tracking, and finally visualizing results. The innovation lies in creating a comprehensive healthcare ecosystem framework and an application that not only aids in COVID-19 diagnosis but also addresses broader health challenges. The main objective is to introduce a novel framework designed to simplify the development and construction of applications by standardizing essential components required for applications focused on addressing diseases. CronaSona includes two parts, which are stakeholders and shared components, and four subsystems: (1) the management information subsystem, (2) the expert subsystem, (3) the COVID-19 detection and forecasting subsystem, and (4) the mobile tracker subsystem. In the proposed framework, a CronaSona app. was built to try to put the virus under control. It is a reactive mobile application for all users, especially COVID-19 patients and doctors. It aims to provide a reliable diagnostic tool for COVID-19 using deep learning techniques, accelerating diagnosis and referral processes, and focuses on forecasting the transmission of COVID-19. It also includes a mobile tracker subsystem for monitoring potential carriers and minimizing the virus spread. It was built to compete with other applications and to help people face the COVID-19 virus. Upon receiving the proposed framework, an application was developed to validate and test the framework's functionalities. The main aim of the developed application, CronaSona app., is to develop and test a reliable diagnostic tool using deep learning techniques to avoid increasing the spread of the disease as much as possible and to accelerate the diagnosis and referral of patients by detecting COVID-19 features from their chest X-ray images. By using CronaSona, human health is saved and stress is reduced by knowing everything about the virus. It performs with the highest accuracy, F1-score, and precision, with consecutive values of 97%, 97.6%, and 96.6%.
本文的主要目的是为 COVID-19 建立一个医疗保健生态系统框架,名为 CronaSona。与仅专注于检测或预测的一些研究不同,CronaSona 旨在提供一个整体解决方案,用于管理数据和/或知识,包括检测、预测、专家建议、治疗建议、实时跟踪,最后是可视化结果。创新之处在于创建了一个全面的医疗保健生态系统框架和一个应用程序,不仅有助于 COVID-19 的诊断,还解决了更广泛的健康挑战。主要目标是引入一种新的框架,通过标准化针对疾病应用程序所需的基本组件,简化应用程序的开发和构建。CronaSona 包括两个部分,即利益相关者和共享组件,以及四个子系统:(1)管理信息子系统,(2)专家子系统,(3)COVID-19 检测和预测子系统,以及(4)移动跟踪器子系统。在提出的框架中,构建了一个 CronaSona 应用程序,以尝试控制病毒。它是一个针对所有用户(特别是 COVID-19 患者和医生)的反应式移动应用程序。它旨在使用深度学习技术为 COVID-19 提供可靠的诊断工具,加速诊断和转诊过程,并专注于预测 COVID-19 的传播。它还包括一个移动跟踪器子系统,用于监测潜在携带者并最大限度地减少病毒传播。它的构建是为了与其他应用程序竞争,并帮助人们应对 COVID-19 病毒。在收到提出的框架后,开发了一个应用程序来验证和测试框架的功能。开发的应用程序 CronaSona 的主要目的是开发和测试使用深度学习技术的可靠诊断工具,以尽可能减少疾病的传播,并通过从胸部 X 射线图像中检测 COVID-19 特征来加速患者的诊断和转诊。通过使用 CronaSona,可以了解有关病毒的所有信息,从而拯救人类健康并减轻压力。它的准确率、F1 分数和精度最高,连续值分别为 97%、97.6%和 96.6%。