Linguistic methods in healthcare application and COVID-19 variants classification.

IF 4.5 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Neural Computing & Applications Pub Date : 2023-01-01 Epub Date: 2021-07-06 DOI:10.1007/s00521-021-06286-y
Marek R Ogiela, Urszula Ogiela
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引用次数: 5

Abstract

One of the most important goals of modern medicine is prevention against pandemic and civilization diseases. For such tasks, advanced IT infrastructures and intelligent AI systems are used, which allow supporting patients' diagnosis and treatment. In our research, we also try to define efficient tools for coronavirus classification, especially using mathematical linguistic methods. This paper presents the ways of application of linguistics techniques in supporting effective management of medical data obtained during coronavirus treatments, and possibilities of application of such methods in classification of different variants of the coronaviruses detected for particular patients. Currently, several types of coronavirus are distinguished, which are characterized by differences in their RNA structure, which in turn causes an increase in the rate of mutation and infection with these viruses.

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医疗保健应用中的语言方法和新冠肺炎变异分类。
现代医学最重要的目标之一是预防流行病和文明疾病。对于这些任务,使用了先进的IT基础设施和智能人工智能系统,为患者的诊断和治疗提供支持。在我们的研究中,我们还试图定义有效的冠状病毒分类工具,特别是使用数学语言方法。本文介绍了应用语言学技术支持有效管理冠状病毒治疗期间获得的医疗数据的方法,以及应用这些方法对特定患者检测到的冠状病毒的不同变体进行分类的可能性。目前,有几种类型的冠状病毒是不同的,其特征是它们的RNA结构不同,这反过来又会导致突变率和感染率的增加。
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来源期刊
Neural Computing & Applications
Neural Computing & Applications 工程技术-计算机:人工智能
CiteScore
11.40
自引率
8.30%
发文量
1280
审稿时长
6.9 months
期刊介绍: Neural Computing & Applications is an international journal which publishes original research and other information in the field of practical applications of neural computing and related techniques such as genetic algorithms, fuzzy logic and neuro-fuzzy systems. All items relevant to building practical systems are within its scope, including but not limited to: -adaptive computing- algorithms- applicable neural networks theory- applied statistics- architectures- artificial intelligence- benchmarks- case histories of innovative applications- fuzzy logic- genetic algorithms- hardware implementations- hybrid intelligent systems- intelligent agents- intelligent control systems- intelligent diagnostics- intelligent forecasting- machine learning- neural networks- neuro-fuzzy systems- pattern recognition- performance measures- self-learning systems- software simulations- supervised and unsupervised learning methods- system engineering and integration. Featured contributions fall into several categories: Original Articles, Review Articles, Book Reviews and Announcements.
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