Fuzzy Logic Assisted Diagnosis for Atherogenesis Risk

Autor:	Juan Antonio Suárez-Cuenca, Oscar A. Rosas-Jaimes, Ana L. Alonso
Rok vydání:	2013
Předmět:	Fuzzy inference system business.industry Total cholesterol Early detection Artificial intelligence Machine learning computer.software_genre business Fuzzy logic computer Algorithm Mathematics
Zdroj:	IFAC Proceedings Volumes. 46:244-248
ISSN:	1474-6670
DOI:	10.3182/20131216-3-in-2044.00031
Popis:	A fuzzy inference system (FIS) that aids in atherogenesis risk diagnosis is described in this document, taken as point of start data of human lipd levels. This FIS uses Total Cholesterol, Low-Density Lipoproteins, Atherogenic Index and Triglycerides as variables in order to propose a diagnosis method to help in low-cost early detection of atherogenesis risk, in strict agreement to medical convention.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::1ddb3b0cd893661b88b2dd67aedee83e https://doi.org/10.3182/20131216-3-in-2044.00031 Zobrazit plný text záznamu