Rough local transfer function for cardiac disorders detection using heart sounds

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86096491" target="_blank" >RIV/61989100:27240/14:86096491 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1093/jigpal/jzv009" target="_blank" >http://dx.doi.org/10.1093/jigpal/jzv009</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1093/jigpal/jzv009" target="_blank" >10.1093/jigpal/jzv009</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Rough local transfer function for cardiac disorders detection using heart sounds

Popis výsledku v původním jazyce

The heart is truly successor to the brain in being the most significant vital organ in the human body. The heart, being a magnificent pump, has its performance orchestrated via a group of valves and highly sophisticated neural control. While the kineticsof the heart are accompanied by sound production, sound waves produced by the heart are reliable diagnostic tools to check heart activity. Chronologically, several data sets have been put forward to observe heart performance and lead to medical intervention whenever necessary. The heart sounds data set utilized in this article provides researchers with an abundance of sound signals classified using different classification algorithms; neural network, rotation forest and random forest are a few that canbe mentioned. This article proposes an approach based on rough sets and a local transfer function classifier for heart valve disease detection. In order to achieve this objective, and to increase the efficiency of the predication model,

Název v anglickém jazyce

Rough local transfer function for cardiac disorders detection using heart sounds

Popis výsledku anglicky

The heart is truly successor to the brain in being the most significant vital organ in the human body. The heart, being a magnificent pump, has its performance orchestrated via a group of valves and highly sophisticated neural control. While the kineticsof the heart are accompanied by sound production, sound waves produced by the heart are reliable diagnostic tools to check heart activity. Chronologically, several data sets have been put forward to observe heart performance and lead to medical intervention whenever necessary. The heart sounds data set utilized in this article provides researchers with an abundance of sound signals classified using different classification algorithms; neural network, rotation forest and random forest are a few that canbe mentioned. This article proposes an approach based on rough sets and a local transfer function classifier for heart valve disease detection. In order to achieve this objective, and to increase the efficiency of the predication model,

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Logic journal of IGPL

ISSN

1367-0751

e-ISSN

—

Svazek periodika

23

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

15

Strana od-do

506-520

Kód UT WoS článku

000357880600014

EID výsledku v databázi Scopus

2-s2.0-84936941835