A comparative study for medical diagnosis of prostate cancer

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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Bibliographic Details
Main Authors: Tuğba Han Simsekler Dizman, Naime Tozlu, Bijan Davvaz, Şaziye Yüksel
Format: Article
Language:English
Published: BİSKA Bilisim Company 2019-03-01
Series:New Trends in Mathematical Sciences
Subjects:
Uncertainty modeling
multi-criteria decision making
prostate cancer
Fuzzy TOPSIS
soft covering approximations.
Online Access:https://ntmsci.com/ajaxtool/GetArticleByPublishedArticleId?PublishedArticleId=8516
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spelling 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
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