Using Machine Learning Algorithms in Cardiovascular Disease Risk Evaluation

Autor:	D. A. Sitar-Taut, D. Pop, D. Zdrenghea, A. V. Sitar-Taut
Jazyk:	angličtina
Rok vydání:	2009
Předmět:	cardiovascular disease machine learning algorithms Mathematics QA1-939 Electronic computers. Computer science QA75.5-76.95
Zdroj:	Journal of Applied Computer Science & Mathematics, Vol 3, Iss 5, Pp 29-32 (2009)
Druh dokumentu:	article
ISSN:	2066-4273 2066-3129
Popis:	Even if Medicine and Computer Science seemapparently intangible domains, they collaborate each otherfor few decades. One of the faces of this cooperation is DataMining, a relative new and multidisciplinary field capable toextract valuable information from large sets of data. Despitethis fact, in cardiology related studies it was rarely used. Weassume that some data mining tools can be used as asubstitute for some complex, expensive, uncomfortable, timeconsuming, and sometimes dangerous medical examinations.This paper aims to show that cardiovascular diseases may bepredicted by classical risk factors analyzed and processed ina “non-invasive” way.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/275abbd3182347f49998c192545454e6 Zobrazit plný text záznamu View record in DOAJ