Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2021, Cilt: 9 Sayı: 1, 125 - 142, 30.06.2021
https://doi.org/10.17093/alphanumeric.949958

Öz

Kaynakça

  • Aggarwal, C. C., & Reddy, C. K. (2014). Data Clustering: Algorithms and Applications. Chapman&Hall/CRC Data Mining and Knowledge Discovery Series, London.
  • Alhamed, A., Lakshmivarahan, S., & Stensrud, D. J. (2002). Cluster analysis of multimodel ensemble data from SAMEX. Monthly weather review, 130(2), 226-256.
  • Altın, E. (2021). Türkiye’ de İller Bazında Ulaşım Faaliyetlerinin Gelişim Durumunun Kümeleme Analizi ile Belirlenmesi (Yüksek Lisans Tezi), Manisa Celal Bayar Üniversitesi Sosyal Bilimler Enstitüsü, Manisa.
  • Australian Institute of Health and Walfare, 2021. Cancer Data in Avustralia. Retrieved from https://www.aihw.gov.au/reports/cancer/cancer-data-in-australia/data?page=1, (Accessed Date:: 12.03.2021).
  • Bulut, H. (2018). R Uygulamaları ile Çok Değişkenli İstatistiksel Yöntemler, Ankara: Nobel Akademik Yayıncılık Eğitim Danışmanlık Tic. Ltd. Şti.
  • Bulut, H. (2019). Türkiye'deki İllerin Yaşam Endekslerine Göre Kümelenmesi. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 23(1), 74-82.
  • Carvalho, P. R., Munita, C. S., & Lapolli, A. L. (2019). Validity Studies Among Hierarchical Methods of Cluster Analysis Using Cophenetic Correlation Coefficient. Brazilian Journal of Radiation Sciences, 7(2A).
  • Cormack, R. M. (1971). A Review of Classification. Journal of the Royal Statistical Society: Series A (General), 134(3), 321-353.
  • Dahl, T., & Næs, T. (2004). Outlier and Group Detection in Sensory Panels Using Hierarchical Cluster Analysis with the Procrustes Distance. Food Quality and Preference, 15(3), 195-208.
  • Demircioğlu, M., & Eşiyok, S. (2020). Covıd–19 Salgını ile Mücadelede Kümeleme Analizi ile Ülkelerin Sınıflandırılması. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 19(37), 369-389.
  • Drachenberg, D., Awe, J. A., Rangel Pozzo, A., Saranchuk, J., & Mai, S. (2019). Advancing Risk Assessment of İntermediate Risk Prostate Cancer Patients. Cancers, 11(6), 855.
  • Greenawalt, D. M., Duong, C., Smyth, G. K., Ciavarella, M. L., Thompson, N. J., Tiang, T., ... & Phillips, W. A. (2007). Gene Expression Profiling of Esophageal Cancer: Comparative Analysis of Barrett's Esophagus, Adenocarcinoma, and Squamous Cell Carcinoma. International Journal Of Cancer, 120(9), 1914-1921.
  • Grimm, L. G., & Yarnold, P. R. (2000). Reading and Understanding More Multivariate Statistics. American Psychological Association.
  • Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1999). Multivariate Data Analysis, Fifth Edition, Prentice Hall International Editions, New Jersey.
  • Hofman, I., & Jarvis, R. (1998, August). Robust and Efficient Cluster Analysis Using a Shared Near Neighbours Approach. In Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No. 98EX170) (Vol. 1, pp. 243-247). IEEE.
  • Hofman, I., & Jarvis, R. (1998, August). Robust and Efficient Cluster Analysis Using a Shared Near Neighbours Approach. In Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No. 98EX170) (Vol. 1, pp. 243-247). IEEE.
  • İlkin, S., Aytar, O., Gençtürk, T. H., & Şahin, S. (2020). Dermoskopik Görüntülerde Lezyon Bölütleme İşlemlerinde K-Ortalama Kümeleme Algoritmasının Kullanımı. Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım Ve Teknoloji, 8(1), 182-191.
  • İncekırık, A. (2005). Çok Değişkenli İstatistiksel Bir Boyut İndirgeme Yöntemi Olarak Kümeleme Analizi ve Bir Uygulama. (Yüksek Lisans Tezi). Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü, İzmir.
  • Jackson, B.B. (1983). Multivariate Data Analysis, Richard D. Irwın, Inc., Homewood, Illinois.
  • Johnson, R. A., & Wichern, D. W. (1998). Applied Multivariate Statistical Analysis (Vol. 4, No. 8). Upper Saddle River, Nj: Prentice Hall.
  • Kent, J. T., Bibby, J., & Mardia, K. V. (1979). Multivariate Analysis. Academic Press, London.
  • Lessig, V. P. (1972). Comparing Cluster Analyses with Cophenetic Correlation. Journal of Marketing Research, 9(1), 82-84.
  • Mathieu, Richard G. (1991). Proceedings of the Portland. International Conference on Management of Engineering and Technology, Portland.
  • Na, L., Wensheng, G., Kexiong, T., & Xiaoning, W. (2002, October). Application of a Combinatorial Neural Network Model Based On Cluster Analysis in Transformer Fault Diagnosis. In 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering. TENCOM'02. Proceedings. (Vol. 3, pp. 1873-1876). IEEE.
  • Seber, G. A. (2009). Multivariate Observations (Vol. 252). John Wiley & Sons.
  • Sharma, S. (1996). Applied Multivariate Techniques. John Wiley and Sons, Inc., New York.
  • Sonğur, C. (2016). Sağlık Göstergelerine Göre Ekonomik Kalkınma ve İşbirliği Örgütü Ülkelerinin Kümeleme Analizi. SGD-Sosyal Güvenlik Dergisi, 6(1), 197-224.
  • Stockburger, D. W. (1998). Multivariate Statistics: Concepts, Models, and Applications. David W. Stockburger.
  • Stundzaite-Barsauskiene, G., Tutkuviene, J., Barkus, A., Jakimaviciene, E. M., Gibaviciene, J., Jakutis, N., ... & Dadoniene, J. (2019). Facial perception, Self-Esteem and Psychosocial Well-Being in Patients After Nasal Surgery Due to Trauma, Cancer and Aesthetic Needs (Cluster Analysis of Multiple İnterrelations). Annals of Human Biology, 46(7-8), 537-552.
  • Tekin, B. (2020). Covıd-19 Pandemisi Döneminde Ülkelerin Covıd-19, Sağlık ve Finansal Göstergeler Bağlamında Sınıflandırılması: Hiyerarşik Kümeleme Analizi Yöntemi. Finans Ekonomi ve Sosyal Araştırmalar Dergisi, 5(2), 336-349.
  • Toms, M. L., Cummings-Hill, M. A., Curry, D. G., & Cone, S. M. (2001). Using Cluster Analysis for Deriving Menu Structures for Automotive Mobile Multimedia Applications. SAE transactions, 265-271.
  • Yılmaz, F., & Söyük, S. Sağlık Risk Faktörlerine Göre Ülkelerin Kümelenmesi ve Çok Kriterli Karar Verme Teknikleriyle Sağlık Durumu Göstergelerinin Analizi. Sosyal Güvence, (17), 283-320.

Classification of Cancer Types by Cluster Analysis Methods

Yıl 2021, Cilt: 9 Sayı: 1, 125 - 142, 30.06.2021
https://doi.org/10.17093/alphanumeric.949958

Öz

Abstract
Cluster analysis can be defined as the group of methods that aim to classify multivariate observations by using similarity/dissimilarity measures between observations. The clusters obtained as a result of the analysis are required to be homogeneous within themselves and heterogeneous among themselves. This study aims to cluster cancer types in datasets created by considering age group characteristics according to gender. In the study, clustering analysis was applied to four different datasets created from the data registered between 1982 and 2016 for 57 cancer types in men and women according to age groups at the Australian Institute of Health and Welfare, and the analysis results were evaluated and interpreted. In addition, in determining the clustering method and the number of clusters, Cophenetic correlation coefficients and 26 cluster validity indices were used, respectively. The distribution of cancer types in age groups determined by gender was observed in 4 different datasets created with 3 different age group characteristics that led to the best separation of cancer groups, and the clustering tendencies of cancers in the relevant age groups were investigated. R-3.5.1 package program was used for analyses. In this study, the analysis results of the k-means method and the average linkage method, which was decided to be the most successful method due to the high cophenetic correlation coefficient value, were evaluated and interpreted. The number of clusters was determined as 3 with the help of cluster validity indices. When the results obtained are examined, it is seen that breast cancer in women and prostate cancer in men is the most common type of cancer in the age group of 40 and above, and that these cancers are alone in a cluster. In addition, it is seen that the 0-14 age group characteristic fails to separate the clusters.

Kaynakça

  • Aggarwal, C. C., & Reddy, C. K. (2014). Data Clustering: Algorithms and Applications. Chapman&Hall/CRC Data Mining and Knowledge Discovery Series, London.
  • Alhamed, A., Lakshmivarahan, S., & Stensrud, D. J. (2002). Cluster analysis of multimodel ensemble data from SAMEX. Monthly weather review, 130(2), 226-256.
  • Altın, E. (2021). Türkiye’ de İller Bazında Ulaşım Faaliyetlerinin Gelişim Durumunun Kümeleme Analizi ile Belirlenmesi (Yüksek Lisans Tezi), Manisa Celal Bayar Üniversitesi Sosyal Bilimler Enstitüsü, Manisa.
  • Australian Institute of Health and Walfare, 2021. Cancer Data in Avustralia. Retrieved from https://www.aihw.gov.au/reports/cancer/cancer-data-in-australia/data?page=1, (Accessed Date:: 12.03.2021).
  • Bulut, H. (2018). R Uygulamaları ile Çok Değişkenli İstatistiksel Yöntemler, Ankara: Nobel Akademik Yayıncılık Eğitim Danışmanlık Tic. Ltd. Şti.
  • Bulut, H. (2019). Türkiye'deki İllerin Yaşam Endekslerine Göre Kümelenmesi. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 23(1), 74-82.
  • Carvalho, P. R., Munita, C. S., & Lapolli, A. L. (2019). Validity Studies Among Hierarchical Methods of Cluster Analysis Using Cophenetic Correlation Coefficient. Brazilian Journal of Radiation Sciences, 7(2A).
  • Cormack, R. M. (1971). A Review of Classification. Journal of the Royal Statistical Society: Series A (General), 134(3), 321-353.
  • Dahl, T., & Næs, T. (2004). Outlier and Group Detection in Sensory Panels Using Hierarchical Cluster Analysis with the Procrustes Distance. Food Quality and Preference, 15(3), 195-208.
  • Demircioğlu, M., & Eşiyok, S. (2020). Covıd–19 Salgını ile Mücadelede Kümeleme Analizi ile Ülkelerin Sınıflandırılması. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 19(37), 369-389.
  • Drachenberg, D., Awe, J. A., Rangel Pozzo, A., Saranchuk, J., & Mai, S. (2019). Advancing Risk Assessment of İntermediate Risk Prostate Cancer Patients. Cancers, 11(6), 855.
  • Greenawalt, D. M., Duong, C., Smyth, G. K., Ciavarella, M. L., Thompson, N. J., Tiang, T., ... & Phillips, W. A. (2007). Gene Expression Profiling of Esophageal Cancer: Comparative Analysis of Barrett's Esophagus, Adenocarcinoma, and Squamous Cell Carcinoma. International Journal Of Cancer, 120(9), 1914-1921.
  • Grimm, L. G., & Yarnold, P. R. (2000). Reading and Understanding More Multivariate Statistics. American Psychological Association.
  • Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1999). Multivariate Data Analysis, Fifth Edition, Prentice Hall International Editions, New Jersey.
  • Hofman, I., & Jarvis, R. (1998, August). Robust and Efficient Cluster Analysis Using a Shared Near Neighbours Approach. In Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No. 98EX170) (Vol. 1, pp. 243-247). IEEE.
  • Hofman, I., & Jarvis, R. (1998, August). Robust and Efficient Cluster Analysis Using a Shared Near Neighbours Approach. In Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No. 98EX170) (Vol. 1, pp. 243-247). IEEE.
  • İlkin, S., Aytar, O., Gençtürk, T. H., & Şahin, S. (2020). Dermoskopik Görüntülerde Lezyon Bölütleme İşlemlerinde K-Ortalama Kümeleme Algoritmasının Kullanımı. Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım Ve Teknoloji, 8(1), 182-191.
  • İncekırık, A. (2005). Çok Değişkenli İstatistiksel Bir Boyut İndirgeme Yöntemi Olarak Kümeleme Analizi ve Bir Uygulama. (Yüksek Lisans Tezi). Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü, İzmir.
  • Jackson, B.B. (1983). Multivariate Data Analysis, Richard D. Irwın, Inc., Homewood, Illinois.
  • Johnson, R. A., & Wichern, D. W. (1998). Applied Multivariate Statistical Analysis (Vol. 4, No. 8). Upper Saddle River, Nj: Prentice Hall.
  • Kent, J. T., Bibby, J., & Mardia, K. V. (1979). Multivariate Analysis. Academic Press, London.
  • Lessig, V. P. (1972). Comparing Cluster Analyses with Cophenetic Correlation. Journal of Marketing Research, 9(1), 82-84.
  • Mathieu, Richard G. (1991). Proceedings of the Portland. International Conference on Management of Engineering and Technology, Portland.
  • Na, L., Wensheng, G., Kexiong, T., & Xiaoning, W. (2002, October). Application of a Combinatorial Neural Network Model Based On Cluster Analysis in Transformer Fault Diagnosis. In 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering. TENCOM'02. Proceedings. (Vol. 3, pp. 1873-1876). IEEE.
  • Seber, G. A. (2009). Multivariate Observations (Vol. 252). John Wiley & Sons.
  • Sharma, S. (1996). Applied Multivariate Techniques. John Wiley and Sons, Inc., New York.
  • Sonğur, C. (2016). Sağlık Göstergelerine Göre Ekonomik Kalkınma ve İşbirliği Örgütü Ülkelerinin Kümeleme Analizi. SGD-Sosyal Güvenlik Dergisi, 6(1), 197-224.
  • Stockburger, D. W. (1998). Multivariate Statistics: Concepts, Models, and Applications. David W. Stockburger.
  • Stundzaite-Barsauskiene, G., Tutkuviene, J., Barkus, A., Jakimaviciene, E. M., Gibaviciene, J., Jakutis, N., ... & Dadoniene, J. (2019). Facial perception, Self-Esteem and Psychosocial Well-Being in Patients After Nasal Surgery Due to Trauma, Cancer and Aesthetic Needs (Cluster Analysis of Multiple İnterrelations). Annals of Human Biology, 46(7-8), 537-552.
  • Tekin, B. (2020). Covıd-19 Pandemisi Döneminde Ülkelerin Covıd-19, Sağlık ve Finansal Göstergeler Bağlamında Sınıflandırılması: Hiyerarşik Kümeleme Analizi Yöntemi. Finans Ekonomi ve Sosyal Araştırmalar Dergisi, 5(2), 336-349.
  • Toms, M. L., Cummings-Hill, M. A., Curry, D. G., & Cone, S. M. (2001). Using Cluster Analysis for Deriving Menu Structures for Automotive Mobile Multimedia Applications. SAE transactions, 265-271.
  • Yılmaz, F., & Söyük, S. Sağlık Risk Faktörlerine Göre Ülkelerin Kümelenmesi ve Çok Kriterli Karar Verme Teknikleriyle Sağlık Durumu Göstergelerinin Analizi. Sosyal Güvence, (17), 283-320.
Toplam 32 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yöneylem
Bölüm Makaleler
Yazarlar

Aynur İncekırık 0000-0002-5029-6036

Öznur İşçi Güneri 0000-0003-3677-7121

Burcu Durmuş 0000-0002-0298-0802

Yayımlanma Tarihi 30 Haziran 2021
Gönderilme Tarihi 9 Haziran 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 9 Sayı: 1

Kaynak Göster

APA İncekırık, A., İşçi Güneri, Ö., & Durmuş, B. (2021). Classification of Cancer Types by Cluster Analysis Methods. Alphanumeric Journal, 9(1), 125-142. https://doi.org/10.17093/alphanumeric.949958

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