A comparative study for medical diagnosis of prostate cancer
In recent years great attention has been paid to studies on artificial intelligence since it can be applied easily to several areas like medical diagnosis, engineering and economics, among others. In this paper we present an example in medicine which aims to find the patients with high prostate can...
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BİSKA Bilisim Company
2019-03-01
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doaj-5b45d21815e946c7b145fc75db143ac42020-11-24T21:07:18ZengBİSKA Bilisim CompanyNew Trends in Mathematical Sciences2147-55202147-55202019-03-017110211210.20852/ntmsci.2019.3478516A comparative study for medical diagnosis of prostate cancerTuğba Han Simsekler Dizman0Naime Tozlu1Bijan Davvaz2Şaziye Yüksel3Gaziantep UniversityNigde UniversityYazd UniversitySelçuk UniversityIn recent years great attention has been paid to studies on artificial intelligence since it can be applied easily to several areas like medical diagnosis, engineering and economics, among others. In this paper we present an example in medicine which aims to find the patients with high prostate cancer risk using a multi-criteria decision making method. Also we compare this method with another method which we studied before. We discuss which method is more convenient. Our datas are prostate specific antigen (PSA), free prostate specific antigen (fPSA), prostate volume (PV) and age factors of 78 patients from Selcuk University Meram Medicine Faculty.https://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8516Uncertainty modelingmulti-criteria decision makingprostate cancerFuzzy TOPSISsoft covering approximations. |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Tuğba Han Simsekler Dizman Naime Tozlu Bijan Davvaz Şaziye Yüksel |
spellingShingle |
Tuğba Han Simsekler Dizman Naime Tozlu Bijan Davvaz Şaziye Yüksel A comparative study for medical diagnosis of prostate cancer New Trends in Mathematical Sciences Uncertainty modeling multi-criteria decision making prostate cancer Fuzzy TOPSIS soft covering approximations. |
author_facet |
Tuğba Han Simsekler Dizman Naime Tozlu Bijan Davvaz Şaziye Yüksel |
author_sort |
Tuğba Han Simsekler Dizman |
title |
A comparative study for medical diagnosis of prostate cancer |
title_short |
A comparative study for medical diagnosis of prostate cancer |
title_full |
A comparative study for medical diagnosis of prostate cancer |
title_fullStr |
A comparative study for medical diagnosis of prostate cancer |
title_full_unstemmed |
A comparative study for medical diagnosis of prostate cancer |
title_sort |
comparative study for medical diagnosis of prostate cancer |
publisher |
BİSKA Bilisim Company |
series |
New Trends in Mathematical Sciences |
issn |
2147-5520 2147-5520 |
publishDate |
2019-03-01 |
description |
In recent years great attention has been paid to studies on artificial intelligence since it can be applied easily to several areas like medical diagnosis, engineering and economics, among others. In this paper we present an example in medicine which aims to find the patients with high prostate cancer risk using a multi-criteria decision making method. Also we compare this method with another method which we studied before. We discuss which method is more convenient. Our datas are prostate specific antigen (PSA), free prostate specific antigen (fPSA), prostate volume (PV) and age factors of 78 patients from Selcuk University Meram Medicine Faculty. |
topic |
Uncertainty modeling multi-criteria decision making prostate cancer Fuzzy TOPSIS soft covering approximations. |
url |
https://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8516 |
work_keys_str_mv |
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