COVID-19 Medical Data Integration Approach

V. Todorova, Veska Gancheva, V. Mladenov
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Abstract

The need to create automated methods for extracting knowledge from data arises from the accumulation of a large amount of data. This paper presents a conceptual model for integrating and processing medical data in three layers, comprising a total of six phases: a model for integrating, filtering, sorting and aggregating Covid-19 data. A medical data integration workflow was designed, including steps of data integration, filtering and sorting. The workflow for Covid-19 medical data from clinical records of 20400 potential patients was employed.
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COVID-19医疗数据集成方法
由于大量数据的积累,需要创建从数据中提取知识的自动化方法。本文提出了一个三层医疗数据整合与处理的概念模型,共包括六个阶段:新冠肺炎数据的整合、过滤、排序和聚合模型。设计了一个医疗数据集成工作流,包括数据集成、过滤和排序步骤。采用20400例潜在患者临床记录中的新冠肺炎医疗数据工作流。
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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