JSM推理应用于新冠肺炎被测者数据的结果分析

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2023-03-03 DOI:10.3103/S0005105522060024

E. A. Efimova

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引用次数: 2

摘要

本文描述了将JSM推理应用于新冠肺炎受试者症状形成的数据的结果。我们构造了对象和假设的图，并考虑了稳定的顶点集。我们还发现了从新冠肺炎中康复的受试者的所有最小亚群，以及所有康复受试者共同具有的所有最小症状亚群，这些症状可能是疾病的迹象。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Analysis of Results of JSM Reasoning Applied to Covid-19 Testees’ Data

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Analysis of Results of JSM Reasoning Applied to Covid-19 Testees’ Data

The paper describes the results of JSM reasoning applied to COVID-19 testees’ data formed from their symptoms. We construct graphs of objects and hypotheses and consider stable sets of vertices. We also find all minimal subsets of those testees who have recovered from COVID-19 and collectively have all groups of symptoms that are possible signs of the disease, as well as all minimal sets of subgroups of symptoms such that all recovered testees collectively have.

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来源期刊

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS COMPUTER SCIENCE, INFORMATION SYSTEMS-

自引率

40.00%

发文量

期刊介绍： Automatic Documentation and Mathematical Linguistics is an international peer reviewed journal that covers all aspects of automation of information processes and systems, as well as algorithms and methods for automatic language analysis. Emphasis is on the practical applications of new technologies and techniques for information analysis and processing.