M. I. Zabezhailo, M. A. Mikheyenkova, Yu. Yu. Trunin
{"title":"On the Nonbinary Version of the Causality Relation in the Intelligent Analysis of Oncological Data","authors":"M. I. Zabezhailo, M. A. Mikheyenkova, Yu. Yu. Trunin","doi":"10.3103/s0005105524700146","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The experience and specifics of the use of intelligent data analysis (IDA) in high-tech medical diagnostics are discussed. The current version of the IDA is a mathematical formalization of the so-called causal similarity heuristic by algebraic means. The main features and abilities of the developed approach are demonstrated in relation to the tasks of the diagnosis and treatment of certain types of human brain tumors. Some results characterizing the causality of the effect of pseudo-progression and tumor recurrence are presented. The potential and prospects of the developed approaches and diagnostic tools in the arsenal of modern evidence-based medicine are considered.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3103/s0005105524700146","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
The experience and specifics of the use of intelligent data analysis (IDA) in high-tech medical diagnostics are discussed. The current version of the IDA is a mathematical formalization of the so-called causal similarity heuristic by algebraic means. The main features and abilities of the developed approach are demonstrated in relation to the tasks of the diagnosis and treatment of certain types of human brain tumors. Some results characterizing the causality of the effect of pseudo-progression and tumor recurrence are presented. The potential and prospects of the developed approaches and diagnostic tools in the arsenal of modern evidence-based medicine are considered.
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.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
