Библиографическое описание:Evolutionary algorithm for automated formation of decision-making models for predicting the safety of opioid therapy : доклад, тезисы доклада / L. V. Lipinskiy [et al.]. - [S. l. : s. n.], 2021. - Текст : непосредственный // IOP Conference Series: Materials Science and Engineering / Krasnoyarsk Science and Technology City Hall. ; III International Conference on Advanced Technologies in Aerospace, Mechanical and Automation Engineering - MIST: Aerospace-III-2020; 9-th International Workshop on Mathematical Models and their Applications (IWMMA-2020) (2020 ; 20.11 - 21.11 ; Krasnoyarsk). - Krasnoyarsk, Russian Federation : IOP Publishing Ltd, 2021. - 1047. - P. 12126. - DOI 10.1088/1757-899X/1047/1/012126.
Аннотация:In this paper, an evolutionary algorithm for solving the problem of predicting the safety of opioid therapy for patients with pancreatic cancer is proposed. Opioid analgesics such as fentanyl and morphine are used as a therapy for pain syndromes. Using the patient database, based on the results of the therapy applied to them, it is determined whether there is a correlation between the outcome and the combination of input data taken into account. To find a set of informative features, it is proposed to use the genetic algorithm for multi-criterion optimization, in which two criteria are reduced to one generalized criterion using the method of "additive convolution". The formed combination of the selected input features, which affects the outcome, is used to build a decision support model and to evaluate it afterwards.
Источник:IOP Conference Series: Materials Science and Engineering
Выпуск:1047
Мероприятие:III International Conference on Advanced Technologies in Aerospace, Mechanical and Automation Engineering - MIST: Aerospace-III-2020; 9-th International Workshop on Mathematical Models and their Applications (IWMMA-2020) (Krasnoyarsk, 2020 ; 20.11 - 21.11)
Номера страниц:12126
Держатель оригинала документа:Bekhterev National Medical Research Center of Psychiatry and Neurology, Ministry of Health of Russia, Peoples' Friendship University of Russia, Prof. V. F. Voino-Yasenetsky Krasnoyarsk State Medical University, Reshetnev Siberian State University of Science and Technology
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