Artificial Neural Networks in Dermatology

被引：0

作者：

Konnov, P. E. ^{[1
]}

Eskov, V. V. ^{[2
]}

Filatov, M. A. ^{[2
]}

Gavrilenko, T. V. ^{[2
]}

机构：

[1] Samara State Med Univ, St Chapaevskaya 89, Samara 443099, Russia

[2] Surgut State Univ, Lenina Pr 1, Surgut 628400, Russia

来源：

DATA SCIENCE AND ALGORITHMS IN SYSTEMS, 2022, VOL 2 | 2023年 / 597卷

关键词：

Artificial neural network; Chronic actinic dermatitis; Uncertainty; The Eskov-Zinchenko effect;

D O I：

10.1007/978-3-031-21438-7_78

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

At the beginning of the 21st century, the Eskov-Zinchenko effect was proved as the sample's uniqueness of any of the human body functions' parameter. Such statistical uncertainty completes the further use of statistics in medicine. Moreover, theway to find the main diagnostic signs (order parameters) inmedicine is not known now. In this regard, it is supposed to use an artificial neural network to distinguish between samples and find order parameters. The article presents a typical example of solving such a problem in dermatology by the diagnosis of actinic dermatitis.

引用

页码：921 / 925

页数：5