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SCI-Expanded JCR Q1 Özgün Makale Scopus
Prediction of Breast Cancer Using Artificial Neural Networks
Journal of Medical Systems 2011 Cilt 36 Sayı 5
Scopus Eşleşmesi Bulundu
61
Atıf
36
Cilt
2901-2907
Sayfa
Scopus Yazarları: Ismail Saritas
Özet
In this study, an artificial neural network (ANN) was developed to determine whether patients have breast cancer or not. Whether patients have cancer or not and if they have its type can be determined by using ANN and BI-RADS evaluation and based on the age of the patient, mass shape, mass border and mass density. Though this system cannot diagnose cancer conclusively, it helps physicians in deciding whether a biopsy is required by providing information about whether the patient has breast cancer or not. Data obtained from 800 patients who were diagnosed with cancer definitively through biopsy. The definitive diagnosis corresponding to each patient and the data from ANN model results were investigated using Confusion matrix and ROC analyses. In the test data of the ANN model that was implemented as a result of these analyses, disease prediction rate was 90.5% and the health ratio was 80.9%. It is seen from these high predictive values that the ANN model is fast, reliable and without any risks and therefore can be of great help to physicians. © 2011 Springer Science+Business Media, LLC.
Anahtar Kelimeler (Scopus)
Artificial neural network BI-RADS Breast cancer Breast cancer prediction
Scimago Dergi Bilgisi Otomatik ISSN Eşleştirmesi 2011 yılı verileri
Journal of Medical Systems
Q3
SJR Quartile
0,356
SJR Skoru
120
H-Index
Kategoriler: Health Informatics (Q3) · Health Information Management (Q3) · Information Systems (Q3) · Medicine (miscellaneous) (Q3)
Alanlar: Computer Science · Health Professions · Medicine
Ülke: United States · Springer New York
Bu bilgiler makale yılına göre Scimago veritabanından ISSN eşleştirmesiyle otomatik getirilmektedir. Dergi sıralama verileri Scimago'nun ilgili yılı baz alınmaktadır.

Anahtar Kelimeler

Artificial neural network BI-RADS Breast cancer Breast cancer prediction

Makale Bilgileri

Dergi Journal of Medical Systems
ISSN 0148-5598
Yıl 2011 / 8. ay
Cilt / Sayı 36 / 5
Sayfalar 2901 – 2907
Makale Türü Özgün Makale
Hakemlik Hakemli
Endeks SCI-Expanded
JCR Quartile Q1
YÖKSİS Atıf 20
Yayın Dili İngilizce
Kapsam Uluslararası
Toplam Yazar 1 kişi
Erişim Türü Basılı+Elektronik
Erişim Linki Makaleye Git
Alan Mühendislik Temel Alanı Elektrik-Elektronik ve Haberleşme Mühendisliği Devreler ve Sistemler Teorisi Yapay Zeka

YÖKSİS Yazar Kaydı

Yazar Adı SARITAŞ İSMAİL
YÖKSİS ID 799744

Metrikler

YÖKSİS Atıf 20
Scopus Atıf 61
JCR Quartile Q1
Yazar Sayısı 1