Academic Journal

Using neural network for simulations to improve the quality of disease diagnosis: Technical aspects

التفاصيل البيبلوغرافية
العنوان: Using neural network for simulations to improve the quality of disease diagnosis: Technical aspects
المؤلفون: Gilev, D. V., Loginovsky, O. V.
المصدر: International Journal of Advanced Trends in Computer Science and Engineering
بيانات النشر: World Academy of Research in Science and Engineering
سنة النشر: 2020
المجموعة: Ural Federal University (URFU): ELAR / Уральский федеральный университет: электронный архив УрФУ
مصطلحات موضوعية: IMPROVE, NEURAL NETWORK, QUALITY, SIMULATIONS
الوصف: Mathematical models are important for the processes of cognition and decision-making. They provide a concise representation of significant relationships in the description of objects and situations. Adding new relationships leads to narrowing the scope of applicability of the model. The formula is an example of a compressed description of a potentially infinite set of objects and situations. Knowledge processing is based on the use of mathematical methods. In this case, it is the most thorough, at least from the point of view of strict logic and consistent formalization. To process knowledge, we must present it in some form that is convenient for analysis. Thus, when analyzing data and knowledge, we do not use them directly, but their representations. Mathematical models of objects and phenomena are an effective way of representation. This is now the most powerful method of cognition of processes, objects and phenomena. Modeling is a special way of scientific research. A mathematical model of an object is a mathematical structure interpreted within a given domain. © 2020, World Academy of Research in Science and Engineering. All rights reserved.
نوع الوثيقة: article in journal/newspaper
وصف الملف: application/pdf
اللغة: English
تدمد: 2278-3091
Relation: Gilev, D. V. Using neural network for simulations to improve the quality of disease diagnosis: Technical aspects / D. V. Gilev, O. V. Loginovsky. — DOI 10.30534/ijatcse/2020/289942020 // International Journal of Advanced Trends in Computer Science and Engineering. — 2020. — Vol. 4. — Iss. 9. — P. 6156-6159.; https://doi.org/10.30534/ijatcse/2020/289942020; ae22ff1e-3d0e-47e7-adbb-0999a186fa57; http://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=85090296552; http://elar.urfu.ru/handle/10995/90421; 85090296552
DOI: 10.30534/ijatcse/2020/289942020
الاتاحة: http://elar.urfu.ru/handle/10995/90421
https://doi.org/10.30534/ijatcse/2020/289942020
http://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=85090296552
Rights: info:eu-repo/semantics/openAccess
رقم الانضمام: edsbas.CE670E9B
قاعدة البيانات: BASE
الوصف
تدمد:22783091
DOI:10.30534/ijatcse/2020/289942020