Logical analysis of data using linear approximation and heuristic algorithms for gene expression-based diagnostics : доклад, тезисы доклада

Описание

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

Конференция: Hybrid Methods of Modeling and Optimization in Complex Systems (HMMOCS-II-2023); Krasnoyarsk; Krasnoyarsk

Год издания: 2024

Идентификатор DOI: 10.1051/itmconf/20245901012

Аннотация: This research aims to develop a methodology that combines logical analysis of data with a white box model to predict the progression of chronic diseases. Such diseases represent a serious health problem, and accurate prediction and management are essential to improve patients' quality of life. Current machine learning methods such Показать полностьюas deep learning often have high accuracy, but their solutions are ‘black boxes', making them difficult to understand. The research combines the best aspects of both methods to create more accurate and interpretable models for predicting the progression of chronic diseases. The methodology developed is expected to contribute to informative decision-making in medical practice, enrich knowledge in medical research and improve the quality of care for patients with chronic diseases.

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Издание

Журнал: Hybrid Methods of Modeling and Optimization in Complex Systems (HMMOCS-II-2023)

Номера страниц: 1012

Место издания: Krasnoyarsk

Персоны

  • Bartosh Maria (Reshetnev Siberian State University of Science and Technology)
  • Masich Igor (Siberian Federal University)

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