Heart Attack Prediction System Based Neural Arbitration

Abdulkader Helwan

Makale detayları

Heart Attack Prediction System Based Neural Arbitration

Yazarlar:

Abdulkader Helwan

Yayıncı:

The association of science, education and technology

Dergi:

TOJSAT 2015 Vol.5 Issue 2, pp.32-39

Belge Tipi:

Makale

Yayın Tarihi:

7/2016

Belge Dili:

Türkçe

Document ID (Org No.):

2000835898

Sıklık:

Üç Aylık

pISSN:

2146-7390

Özet:

 

Heart attack is an asymptomatic and epidemic medical condition that may suddenly occur and causes “death”. Therefore, it is a life-threatening condition and it should be detected before it occurs. Heart attack is so far predicted using the conventional ways of doctor’s examination and by performing some medical tests such as stress test, ECG, and heart CTScan etc. The coronary vessels constriction, the cholesterol levels in the arteries, and other attributes can be good indicators for making effective decisions. In this paper, a neural network based support decision system is developed for the prediction of heart attack. The proposed system uses 14 medical attributes, obtained from the Cleveland database such as sex, heart rate, and vessels narrowing etc. Two attributes have been emphasized in order to distinguish the heart attack from other heart diseases; the vessels constriction rate and the chest pain type. The testing results show high efficiency and capability for the designed system to predict heart attack and diagnose the three medical conditions: normal, abnormal, and imminent to heart attack.

Makale detayları

Heart Attack Prediction System Based Neural Arbitration

Yazarlar: Abdulkader Helwan

Yayıncı: The association of science, education and technology

Dergi: TOJSAT 2015 Vol.5 Issue 2, pp.32-39

Belge Tipi: Makale

Yayın Tarihi: 7/2016

Belge Dili: Türkçe

Document ID (Org No.): 2000835898

Sıklık: Üç Aylık

pISSN: 2146-7390

Sayı

Yazarlar:

Abdulkader Helwan

Yayıncı:

The association of science, education and technology

Dergi:

TOJSAT 2015 Vol.5 Issue 2, pp.32-39

Belge Tipi:

Makale

Yayın Tarihi:

7/2016

Belge Dili:

Türkçe

Document ID (Org No.):

2000835898

Sıklık:

Üç Aylık

pISSN:

2146-7390