Scopus Eşleşmesi Bulundu
50
Atıf
37
Cilt
6646-6650
Sayfa
Scopus Yazarları: Ismail Saritas, Ilker Ali Ozkan, Unal Sert
Özet
In this study, an artificial neural network has been devised that yields a prognostic result indicating whether patients have cancer or not using their free prostate-specific antigen, total prostate-specific antigen and age data. Though this system does not diagnose cancer conclusively, it helps the doctor in deciding whether a biopsy is necessary by providing information about whether the patient has prostate cancer or not. Data from 121 patients who were definitively diagnosed with cancer after biopsy were used in devising the system. The results of the definitive diagnoses of the patients and the results of the ANN that was performed were analysed using confusion matrix and ROC analyses. As a result of ANN, which was implemented on the basis of these analyses, success rates of 94.11% and 94.44% were achieved for prognosis of disease and validity, respectively. The ANN, which yielded these high rates of reliability, will help doctors make quick and reliable diagnoses without any risks and make it a better option to monitor patients with low prostate cancer risk on whom biopsies must not be carried out through a policy of wait and see. © 2010 Elsevier Ltd. All rights reserved.
Anahtar Kelimeler (Scopus)
Prostate cancer
Prostate-specific antigen
Artificial neural network
Prognosis of prostate cancer
Scimago Dergi Bilgisi
Otomatik ISSN Eşleştirmesi
2010 yılı verileri
Expert Systems with Applications
Q1
SJR Quartile
1,046
SJR Skoru
290
H-Index
Kategoriler: Artificial Intelligence (Q1) · Computer Science Applications (Q1) · Engineering (miscellaneous) (Q1)
Alanlar: Computer Science · Engineering
Ülke: United Kingdom
· Elsevier Ltd
Bu bilgiler makale yılına göre Scimago veritabanından ISSN eşleştirmesiyle otomatik getirilmektedir.
Dergi sıralama verileri Scimago'nun ilgili yılı baz alınmaktadır.
Anahtar Kelimeler
Prostate cancer
Prostate-specific antigen
Artificial neural network
Prognosis of prostate cancer
Makale Bilgileri
Dergi
Expert Systems with Applications
ISSN
0957-4174
Yıl
2010
/ 9. ay
Cilt / Sayı
37
/ 9
Sayfalar
6646 – 6650
Makale Türü
Özgün Makale
Hakemlik
Hakemli
Endeks
SCI-Expanded
JCR Quartile
Q1
YÖKSİS Atıf
30
Yayın Dili
İngilizce
Kapsam
Uluslararası
Toplam Yazar
3 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,ÖZKAN İLKER ALİ,SERT İBRAHİM ÜNAL
YÖKSİS ID
799500
Hızlı Erişim
Metrikler
YÖKSİS Atıf
30
Scopus Atıf
50
JCR Quartile
Q1
Yazar Sayısı
3