Статья

Predictive Modelling of Weight-Loss-Therapy Results for Patients with Obesity.

I. Derevitskii, G. Matveev, E. Vasilieva, A. Babenko, A. Lutsenko,
2021

Obesity is one of the main medical complications around the world. Obesity represents an epidemic: At least 2.8 million people die each year as a result of being obese. Obesity increases the risk of several diseases such as some types of cancer and type 2 diabetes, raises cardiovascular risk. Drug therapy is used to reduce weight. However, the patient often does not have a significant weight loss after taking the drug for a long period. Then doctors prescribe a new drug. Many weight loss drugs are expensive. Therefore, medical professionals need methods to predict the future outcome of taking a drug. This study proposes a method for predicting the future effect of Weight Loss Therapy (WLT) drug on a patient considering his (her) individual health parameters. We propose a method for developing a Decision Support System (DSS) for medical professionals treating obese patients. The study also solves the practical problem of developing a method for predicting the sibutramine future effect. Sibutramine is often used in medical practice. However, doctors need to know that the patient will have significant weight-loss results. Our method has a high quality of prediction. Therefore, it can be used by medical professionals working with obese patients in Russia and other countries. © 2020 Elsevier B.V.. All rights reserved.

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Версии

  • 1. Version of Record от 2021-04-27

Метаданные

Об авторах
  • I. Derevitskii
    Itmo University, Saint Petersburg, Russian Federation
  • G. Matveev
    Almazov National Medical Research Centre, Saint Petersburg, Russian Federation
  • E. Vasilieva
  • A. Babenko
  • A. Lutsenko
Название журнала
  • Procedia Computer Science
Том
  • 178
Страницы
  • 254-263
Ключевые слова
  • Decision support systems; Forecasting; Nutrition; Predictive analytics; Cardiovascular risk; Decision support system (dss); Health parameters; Medical complications; Medical practice; Medical professionals; Practical problems; Predictive modelling; Drug therapy
Издатель
  • Elsevier B.V.
Тип документа
  • Conference Paper
Тип лицензии Creative Commons
  • CC
Правовой статус документа
  • Свободная лицензия
Источник
  • scopus