Application of the Method of Representation of Decision Rules in a Hierarchical Structure for Forecasting and Data Analysis

Описание

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International Conference on Recent Innovations in Computing ICRIC 2023; Jammu, India; Jammu, India

Год издания: 2024

Идентификатор DOI: 10.1007/978-981-97-3442-9_45

Ключевые слова: decision tree, data analysis, health risk, machine learning, diabetes mellitus

Аннотация: Diabetes mellitus stands as a critical global health challenge in the twentyfirst century, with its escalating prevalence impacting individuals worldwide. Its complications significantly diminish both the quality of life and life expectancy, contributing to early disabilities and heightened mortality rates. Effective prediction of Показать полностьюthis disease holds immense value for its early diagnosis and subsequent management. This study focuses on comprehensive data analysis, emphasizing the pivotal role of predictive analytics. Employing decision tree methodology, specifically a hierarchical structure for representation of decision rules, the research explores the application of this approach in forecasting and data analysis within the realm of diabetes mellitus. By delving into this crucial area, the study aims to elucidate the efficacy of decision trees in disease prediction and diagnostic enhancement.

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Издание

Журнал: Proceedings of International Conference on Recent Innovations in Computing (ICRIC 2023)

Выпуск журнала: 1195

Номера страниц: 645-655

Место издания: Singapore

Персоны

  • Kravtsov Kirill I. (Reshetnev Siberian State University of Science and Technology)
  • Kukartsev Vladislav V. (Bauman Moscow State Technical University)
  • Daniel Ageev A. (Bauman Moscow State Technical University)

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