氧:用于患者健康记录管理和药物诊断的分布式医疗保健框架

M. Wickramarathna, K. De Silva, Vihanga Lekamalage, Janith Senanayake, J. Perera, L. Ruggahakotuwa
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引用次数: 0

摘要

随着COVID-19大流行,世界正面临各种医疗保健问题,医疗保健自动化比以往任何时候都更加重要。大流行暴露了现有数字医疗系统在管理突发公共卫生事件方面的局限性。斯里兰卡的许多医疗机构没有注册人口,因此存在沟通缺口。电子健康记录系统(EHRs)在共享患者详细信息方面变得越来越流行,但在保护患者隐私的同时访问多个EHRs中的分散数据仍然是一个挑战。这些医疗记录大多是打印格式,手动将它们输入电子病历系统既耗时又容易出错。药物错误不仅是一个严重的医疗保健问题,而且在大流行期间去看医生进行药物诊断的风险更大。本研究介绍了一种基于区块链的患者健康记录系统、一种基于光学字符识别(OCR)和自然语言处理(NLP)的医疗文档扫描仪、一种基于图像处理的药物标识符和一种由NLP驱动的医疗聊天机器人,作为解决这些问题的四种新方法。与结果一起,本研究旨在为医疗保健中的局限性引入解决方案,同时为全球医疗保健社区提供分布式医疗保健框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Oxygen: A Distributed Health Care Framework for Patient Health Record Management and Pharmaceutical Diagnosis
With the COVID-19 pandemic, the world is confronting various healthcare issues, and healthcare automation is more crucial than ever. The pandemic has revealed the limitations of existing digital healthcare systems to manage public health emergencies. There is no registered population for many healthcare institutions in Sri Lanka, as a result, there is a communication gap. Electronic Health Record systems (EHRs) are becoming popular to share patient details but accessing scattered data across several EHRs while safeguarding patient privacy remains a challenge. Most of these medical records are in printed format and manually entering those into EHR systems is time-consuming and error prone. Not only that pharmaceutical error is a critical healthcare problem, but it is even riskier to visit doctors for pharmaceutical diagnosis during a pandemic. This research introduces a Blockchain-based patient health record system, an Optical Character Recognition (OCR) and Natural Language Processing (NLP) based Medical Document Scanner, a Drug Identifier based on Image Processing and a Medical Chatbot powered by NLP as four novel approaches to address these issues. Altogether with the results, this research aims at introducing a solution for the limitations in healthcare while providing a distributed healthcare framework for the healthcare community worldwide.
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