Integrated e-healthcare management system using machine learning and flask

Sanjeev Kumar, J. Ojha, Mayank Tripathi, Kirtika Garg
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引用次数: 1

Abstract

Healthcare is one of the flourishing sectors in each developed and emerging economy. Due to this vast COVID-19 pandemic, the traditional healthcare system cannot provide adequate facilities due to a lack of interactions between doctors and patients. In such conditions, e-healthcare is contributing towards the accelerating growth within the healthcare industry by providing the latest information technology to support information search and communication processes. Besides this, a machine learning algorithm is used to intensify the smartness of the healthcare industry. The five major components of an e-healthcare system are cost-saving, virtual networking, electronic medical record physician-patient relationships and privacy concerns. Our proposed system provides location-based e-prescribing, e-reports, disease prediction, and suggesting treatments and emergency services with a single click, so it is better than another existing system. Copyright © 2023 Inderscience Enterprises Ltd.
使用机器学习和烧瓶的集成电子医疗管理系统
医疗保健是每个发达经济体和新兴经济体蓬勃发展的行业之一。由于COVID-19的大规模流行,传统的医疗保健系统由于缺乏医患之间的互动而无法提供足够的设施。在这种情况下,电子医疗通过提供最新的信息技术来支持信息搜索和通信流程,为医疗保健行业的加速增长做出了贡献。除此之外,还使用了机器学习算法来加强医疗保健行业的智能。电子医疗保健系统的五个主要组成部分是节约成本、虚拟网络、电子病历医患关系和隐私问题。我们提出的系统提供基于位置的电子处方、电子报告、疾病预测以及建议治疗和紧急服务,只需点击一次,因此比其他现有系统更好。版权所有©2023 Inderscience Enterprises Ltd。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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