Intelligent Decision-Support System for Epidemiological Diagnostics. II. Information Technologies Development*, **

Bazilevych, Kseniia; Chumachenko, Dmytro; Hulianytskyi, L. F.; Meniailov, Ievgen; Yakovlev, Sergiy

doi:10.1007/s10559-022-00484-9

Cited by 2 publications

(1 citation statement)

References 23 publications

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“…Research is part of a complex intelligent information system for epidemiological diagnostics, the concept of which is discussed in [16,17].…”

Section: Introductionmentioning

confidence: 99%

Information system for assessing the informativeness of an epidemic process features

Bazilevych,

Kyrylenko,

Parfenyuk

et al. 2023

SRIT

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The primary objective of this study is to assess the informativeness of various parameters influencing epidemic processes utilizing the Shannon and Kullback–Leibler methods. These methods were selected based on their foundation in the principles of information theory and their extensive application in machine learning, statistics, and other relevant domains. A comparative analysis was performed between the results acquired from both methods, and an information system was designed to facilitate the uploading of data samples and the calculation of factor informativeness impacting the epidemic processes. The findings revealed that certain features, such as “Chronic lung disease,” “Chronic kidney disease,” and “Weakened immunity,” did not carry significant information for further analysis and hindered the forecasting process, as per the data set examined. The developed information system efficiently supports the assessment of feature informativeness, thereby aiding in the comprehensive analysis of epidemic processes and enabling the visualization of the results. This study contributes to the current body of knowledge by providing specific examples of applying the described algorithmic models, comparing various methods and their outcomes, and developing a supportive tool for analyzing epidemic processes.

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“…Research is part of a complex intelligent information system for epidemiological diagnostics, the concept of which is discussed in [16,17].…”

Section: Introductionmentioning

confidence: 99%