An application of decision making problem based on soft expert sets for diagnosing prostate cancer
Yıl 2022,
Cilt: 24 Sayı: 1, 79 - 90, 05.01.2022
Zehra Güzel Ergül
,
Naime Demirtaş
Öz
In this study, a different type of multicriteria decision making method based on soft expert sets is proposed for diagnosing prostate cancer. This method which determines the necessity of biopsy and gives a risk range of prostate cancer is given for comparing results have been obtained from other methods [1, 2, 3]. Consequently, the number of patients that are biopsied is reduced.
Destekleyen Kurum
Kırşehir Ahi Evran University
Proje Numarası
FEF. A4.18.024
Teşekkür
This work is supported by the Kırşehir Ahi Evran University Scientific Research Projects Coordination Unit with project number FEF. A4.18.024
Kaynakça
- Güzel Ergül, Z. and Yüksel, Ş., A new type of soft covering based rough sets applied to multicriteria group decision making for medical diagnosis, Mathematical Sciences and Applications E-Notes, 7 (1): 28-38, (2019).
- Yüksel, Ş., Güzel Ergül, Z. and Tozlu, N., Soft covering based rough sets and their application, The Scientific World Journal, Article ID 970893: 9 pages, http:\\dx.doi:10.1155/2014/970893, (2014).
- Tozlu, N., Dizman (Simsekler), T., Davvaz, B. and Yuksel, S., A comparative study for medical diagnosis of prostate cancer, New Trends in Mathematical Sciences, 7 (1): 102-112, (2019).
- Zadeh, L.A., Fuzzy sets, Inf. Control, 8: 338-353, (1965).
- Pawlak, Z., Rough sets, Int. J. Comput. Inf. Sci., 11: 341-356, (1982).
- Molodtsov, D., Soft set theory-first results, Computers and Mathematics with Applications, 37: 19-31, (1999).
- Alkhazaleh S. and Razak Salleh S., Soft expert sets, Advances in Decision Sciences, Article ID 757868: 12 pages, doi:10.1155/2011/757868, (2011).
- Hassan, N., Uluçay, V. and Şahin, M., Q-Neutrosophic soft expert set and its application in decision making, International Journal of Fuzzy System Applications, 7 (4) : 37- 61, (2018).
- Demir, İ., N-soft mappings with application in medical diagnosis, Mathematical Methods in the Applied Sciences, 44 (8): 7343-7358, (2021).
- Özgür, N.Y. and Taş, N., A note on application of fuzzy soft sets to investment decision making problem, Journal of New Theory, 1(7): 1-10, (2015).
- Kalaichelvi, Dr. A. and Malini, P.H., Application of fuzzy soft sets to investment decision making problem, International Journal of Mathematical Sciences and Applications, 1 (3): 1583-1586, (2011).
- Taş, N., Özgür, N.Y. and Demir, P., An application of soft set and fuzzy soft set theories stock management., Süleyman Demirel University Journal of Natural and Applied Sciences, 21 (3): 791-796, (2017).
- Karaca, F. and Taş, N., Decision making problem for Life and Non-Life insurances, Journal of Balıkesir University Institute of Science and Technology, 20 (1): 572-588, (2018).
- Irkin, R., Özgür, N. Y. and Taş, N., Optimization of lactic acid bacteria viability using fuzzy soft set modelling, An International Journal of Optimization and Control: Theories & Applications, 8 (2): 266-275, (2018).
- Saritas, I., Allahverdi, N. and Sert, U., A fuzzy expert system design for diagnosis of prostate cancer, International Conference on Computer Systems and Technologies-CompSysTech 2003, Sofia, Bulgaria, s. 345-351, 19-20, (2003).
- Benecchi, L., Neuro-fuzzy system for prostate cancer diagnosis, Urology, 68 (2): 357-361, (2006).
- Keles, A., Hasiloglu, A.S., Keles, A. and Aksoy, Y., Neuro-fuzzy classification of prostate cancer using NEFCLASS-J, Computers in Biology and Medicine, 37: 1617-1628, (2007).
- Saritas, I., Ozkan, I.A. and Sert, U., Prognasis of prostate cancer by artficial neural networks, Expert Systems with Applications, 37: 6646-6650, (2010).
- Yuksel, S., Dizman, T., Yıldızdan, G. and Sert, U., Application of soft sets to diagnose the prostate cancer risk, J. Inequal. Appl., 229, (2013).
- Feng, F., Soft rough sets applied to multicriteria group decision making, Annals of Fuzzy Mathematics and Informatics, 2 (1): 69-80, (2011).
- Chen-Tung C. Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy Sets and Systems, 114: 1-9, (2000).
- Molodtsov, D., The theory of soft sets, URSS Publishers, Moscow, (2004).
- Chen, D., Tsang, E.C.C., Yeung, D.S. and Wang, X., The parameterization reduction of soft sets and its applications, Computers and Mathematics with Applications, 49: 757-763, (2005).
- Feng, F., Li, C., Davvaz, B. and Ali, M.I., Soft sets combined with fuzzy sets and rough sets: a tentative approach, Soft Computing, 14: 899-911, (2010).
- Metlin, C., Lee, F. and Drago, J., The American cancer society national prostate cancer detection, project: Findings on the detection of early prostate cancer in 2425 men, Cancer, 67: 2949-2958, (1991).
- Seker, H., Odetayo, M., Petrovic, D. and Naguib, R.N.G., A fuzzy logic based method for prognostic decision making breast and prostate cancers, IEEE Transactions on Information Technology in Biomedicine, 7: 114-122, (2003).
Prostat kanseri teşhisi için soft expert kümelere dayanan karar verme probleminin bir uygulaması
Yıl 2022,
Cilt: 24 Sayı: 1, 79 - 90, 05.01.2022
Zehra Güzel Ergül
,
Naime Demirtaş
Öz
Bu çalışmada soft expert kümelere dayanan farklı bir tip çok kriterli karar verme metodu prostat kanser teşhişi için önerildi. Biyopsinin gerekliliğini belirleyen ve prostat kanser risk oranını veren bu metod, diğer metotlardan [1, 2, 3] elde edilen sonuçlarla karşılaştırma yapmak için verildi. Sonuç olarak biyopsi yapılan hastaların sayısı azaltıldı.
Proje Numarası
FEF. A4.18.024
Kaynakça
- Güzel Ergül, Z. and Yüksel, Ş., A new type of soft covering based rough sets applied to multicriteria group decision making for medical diagnosis, Mathematical Sciences and Applications E-Notes, 7 (1): 28-38, (2019).
- Yüksel, Ş., Güzel Ergül, Z. and Tozlu, N., Soft covering based rough sets and their application, The Scientific World Journal, Article ID 970893: 9 pages, http:\\dx.doi:10.1155/2014/970893, (2014).
- Tozlu, N., Dizman (Simsekler), T., Davvaz, B. and Yuksel, S., A comparative study for medical diagnosis of prostate cancer, New Trends in Mathematical Sciences, 7 (1): 102-112, (2019).
- Zadeh, L.A., Fuzzy sets, Inf. Control, 8: 338-353, (1965).
- Pawlak, Z., Rough sets, Int. J. Comput. Inf. Sci., 11: 341-356, (1982).
- Molodtsov, D., Soft set theory-first results, Computers and Mathematics with Applications, 37: 19-31, (1999).
- Alkhazaleh S. and Razak Salleh S., Soft expert sets, Advances in Decision Sciences, Article ID 757868: 12 pages, doi:10.1155/2011/757868, (2011).
- Hassan, N., Uluçay, V. and Şahin, M., Q-Neutrosophic soft expert set and its application in decision making, International Journal of Fuzzy System Applications, 7 (4) : 37- 61, (2018).
- Demir, İ., N-soft mappings with application in medical diagnosis, Mathematical Methods in the Applied Sciences, 44 (8): 7343-7358, (2021).
- Özgür, N.Y. and Taş, N., A note on application of fuzzy soft sets to investment decision making problem, Journal of New Theory, 1(7): 1-10, (2015).
- Kalaichelvi, Dr. A. and Malini, P.H., Application of fuzzy soft sets to investment decision making problem, International Journal of Mathematical Sciences and Applications, 1 (3): 1583-1586, (2011).
- Taş, N., Özgür, N.Y. and Demir, P., An application of soft set and fuzzy soft set theories stock management., Süleyman Demirel University Journal of Natural and Applied Sciences, 21 (3): 791-796, (2017).
- Karaca, F. and Taş, N., Decision making problem for Life and Non-Life insurances, Journal of Balıkesir University Institute of Science and Technology, 20 (1): 572-588, (2018).
- Irkin, R., Özgür, N. Y. and Taş, N., Optimization of lactic acid bacteria viability using fuzzy soft set modelling, An International Journal of Optimization and Control: Theories & Applications, 8 (2): 266-275, (2018).
- Saritas, I., Allahverdi, N. and Sert, U., A fuzzy expert system design for diagnosis of prostate cancer, International Conference on Computer Systems and Technologies-CompSysTech 2003, Sofia, Bulgaria, s. 345-351, 19-20, (2003).
- Benecchi, L., Neuro-fuzzy system for prostate cancer diagnosis, Urology, 68 (2): 357-361, (2006).
- Keles, A., Hasiloglu, A.S., Keles, A. and Aksoy, Y., Neuro-fuzzy classification of prostate cancer using NEFCLASS-J, Computers in Biology and Medicine, 37: 1617-1628, (2007).
- Saritas, I., Ozkan, I.A. and Sert, U., Prognasis of prostate cancer by artficial neural networks, Expert Systems with Applications, 37: 6646-6650, (2010).
- Yuksel, S., Dizman, T., Yıldızdan, G. and Sert, U., Application of soft sets to diagnose the prostate cancer risk, J. Inequal. Appl., 229, (2013).
- Feng, F., Soft rough sets applied to multicriteria group decision making, Annals of Fuzzy Mathematics and Informatics, 2 (1): 69-80, (2011).
- Chen-Tung C. Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy Sets and Systems, 114: 1-9, (2000).
- Molodtsov, D., The theory of soft sets, URSS Publishers, Moscow, (2004).
- Chen, D., Tsang, E.C.C., Yeung, D.S. and Wang, X., The parameterization reduction of soft sets and its applications, Computers and Mathematics with Applications, 49: 757-763, (2005).
- Feng, F., Li, C., Davvaz, B. and Ali, M.I., Soft sets combined with fuzzy sets and rough sets: a tentative approach, Soft Computing, 14: 899-911, (2010).
- Metlin, C., Lee, F. and Drago, J., The American cancer society national prostate cancer detection, project: Findings on the detection of early prostate cancer in 2425 men, Cancer, 67: 2949-2958, (1991).
- Seker, H., Odetayo, M., Petrovic, D. and Naguib, R.N.G., A fuzzy logic based method for prognostic decision making breast and prostate cancers, IEEE Transactions on Information Technology in Biomedicine, 7: 114-122, (2003).