- Tytuł:
- Attribute selection for stroke prediction
- Autorzy:
- Zdrodowska, Małgorzata
- Powiązania:
- https://bibliotekanauki.pl/articles/386466.pdf
- Data publikacji:
- 2019
- Wydawca:
- Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
- Tematy:
-
data mining
classifier
J48 (C4.5)
CART
PART
naive Bayes classifier
random forest
support vector machine
multilayer perceptron
haemorrhagic stroke
ischemic stroke - Opis:
- Stroke is the third most common cause of death and the most common cause of long-term disability among adults around theworld. Therefore, stroke prediction and diagnosis is a very important issue. Data mining techniques come in handy to help determine the correlations between individual patient characterisation data, that is, extract from the medical information system the knowledge necessary to predict and treat various diseases. The study analysed the data of patients with stroke using eight known classification algorithms (J48 (C4.5), CART, PART, naive Bayes classifier, Random Forest, Supporting Vector Machine and neural networks Multilayer Perceptron), which allowed to build an exploration model given with an accuracy of over 88%. The potential features of patients, which may be factors that increase the risk of stroke, were also indicated.
- Źródło:
-
Acta Mechanica et Automatica; 2019, 13, 3; 200-204
1898-4088
2300-5319 - Pojawia się w:
- Acta Mechanica et Automatica
- Dostawca treści:
- Biblioteka Nauki
Artykuł