Design of A Novel Device Measuring Testicular Consistency, Size and Temperature and Classification Algorithm Analysis of Data Compared to Urologist Examinations

Mehmet Çağrı Soylu; Oğuz Ekmekçioğlu

Makale detayları

Design of A Novel Device Measuring Testicular Consistency, Size and Temperature and Classification Algorithm Analysis of Data Compared to Urologist Examinations

Yazarlar:

Mehmet Çağrı Soylu | Oğuz Ekmekçioğlu

Yayıncı:

Erciyes University

Ana Başlıklar:

Biyomedikal Tanı

Dergi:

Enginoscope Vol.1 Issue 1, pp.60-75

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001342121

pISSN:

3062-2360

Anahtar kelimeler:

Özet:

 Background and Objective: Infertility is a health problem that can be seen all over the world, originating from both men and women. In male infertility, many tests and examinations are performed in order to find the treatment method to solve the problem. The first of these is the physical examination, and the clinician cannot obtain numerical data and make comparisons as a result of this examination. Methods: In this study, it is aimed to design a system that will reveal the physical differences of the testicles, which play an important role in the production of sperm and some special hormones, in about 1 minute. Thanks to this device, temperature, volume and consistency parameters of testicles from 50 different patients of different ages were measured in real time with different sensors on the device. The results were analysed with both statistical analysis and machine learning method. Results: According to the results of this study, it has been revealed that the system designed can help clinicians in testicular examination. In terms of consistency and heat stress, the classification algorithm with the highest accuracy rate according to the 3 different cross validation rates applied is trees and it showed 92.0 accuracy according to validation 5 and 15, but 89.0 according to cross validation 10. In terms of testicle size, Trees and Ensemble with the validation rate of 15 showed the highest accuracy with 89. Conclusions: Although the applied methods showed high accuracy, the specificity rate is not optimal due to data limitations. This is because there is not enough data. It is clear that with more data, both the accuracy rates and the level of specificity will be higher.

 Background and Objective: Infertility is a health problem that can be seen all over the world, originating from both men and women. In male infertility, many tests and examinations are performed in order to find the treatment method to solve the problem. The first of these is the physical examination, and the clinician cannot obtain numerical data and make comparisons as a result of this examination. Methods: In this study, it is aimed to design a system that will reveal the physical differences of the testicles, which play an important role in the production of sperm and some special hormones, in about 1 minute. Thanks to this device, temperature, volume and consistency parameters of testicles from 50 different patients of different ages were measured in real time with different sensors on the device. The results were analysed with both statistical analysis and machine learning method. Results: According to the results of this study, it has been revealed that the system designed can help clinicians in testicular examination. In terms of consistency and heat stress, the classification algorithm with the highest accuracy rate according to the 3 different cross validation rates applied is trees and it showed 92.0 accuracy according to validation 5 and 15, but 89.0 according to cross validation 10. In terms of testicle size, Trees and Ensemble with the validation rate of 15 showed the highest accuracy with 89. Conclusions: Although the applied methods showed high accuracy, the specificity rate is not optimal due to data limitations. This is because there is not enough data. It is clear that with more data, both the accuracy rates and the level of specificity will be higher.

 Background and Objective: Infertility is a health problem that can be seen all over the world, originating from both men and women. In male infertility, many tests and examinations are performed in order to find the treatment method to solve the problem. The first of these is the physical examination, and the clinician cannot obtain numerical data and make comparisons as a result of this examination. Methods: In this study, it is aimed to design a system that will reveal the physical differences of the testicles, which play an important role in the production of sperm and some special hormones, in about 1 minute. Thanks to this device, temperature, volume and consistency parameters of testicles from 50 different patients of different ages were measured in real time with different sensors on the device. The results were analysed with both statistical analysis and machine learning method. Results: According to the results of this study, it has been revealed that the system designed can help clinicians in testicular examination. In terms of consistency and heat stress, the classification algorithm with the highest accuracy rate according to the 3 different cross validation rates applied is trees and it showed 92.0 accuracy according to validation 5 and 15, but 89.0 according to cross validation 10. In terms of testicle size, Trees and Ensemble with the validation rate of 15 showed the highest accuracy with 89. Conclusions: Although the applied methods showed high accuracy, the specificity rate is not optimal due to data limitations. This is because there is not enough data. It is clear that with more data, both the accuracy rates and the level of specificity will be higher.

 Arka Plan ve Amaç: Kısırlık, dünya genelinde erkeklerde ve kadınlarda yaygın olarak görülebilen bir sağlık sorunudur. Erkek infertilitesinde, problemi çözmek için tedavi yöntemini belirlemek amacıyla birçok test ve inceleme yapılmaktadır. Bunların ilki fiziksel muayenedir, ancak bu muayene ile klinisyen çoğunlukla sayısal veriler elde edemez ve gerekli karşılaştırmaları yapamaz. Yöntemler: Bu çalışmada, sperm üretimi ve bazı özel hormonların üretiminde önemli bir rol oynayan testislerin fiziksel farklılıklarını yaklaşık 1 dakika içinde ortaya koyacak bir sistem tasarlanması hedeflenmiştir. Bu cihaz sayesinde, farklı yaşlardan 50 farklı hastanın testislerinin sıcaklık, hacim ve tutarlılık parametreleri, cihazdaki farklı sensörlerle gerçek zamanlı olarak ölçülmüştür. Sonuçlar, hem istatistiksel analiz hem de makine öğrenimi yöntemi ile incelenmiştir. Bulgular: Bu çalışmanın sonuçlarına göre, tasarlanan sistemin, kliniklerde testis muayenesine yardımcı olabileceği ortaya konulmuştur. Tutarlılık ve ısı stresi açısından, uygulanan 3 farklı çapraz doğrulama oranına göre en yüksek doğruluk oranına sahip sınıflandırma algoritması decision trees karar ağaçları olup, doğrulama 5 ve 15e göre 92,0 doğruluk, çapraz doğrulama 10a göre ise 89,0 doğruluk göstermiştir. Testis boyutu açısından ise, karar ağaçları ve ansambl yöntemleri, doğrulama oranı 15e göre en yüksek doğruluk oranı ile 89,0 doğruluk göstermiştir. Sonuç: Uygulanan yöntemler yüksek doğruluk oranları gösterse deveri sınırlamaları nedeniyle özgüllük oranı optimal değildir. Bunun nedeni, örnek sayısının yetersiz olmasıdır. Daha fazla veri ile hem doğruluk oranlarının hem de özgüllük seviyelerinin daha yüksek olacağı düşünülmektedir.

Makale detayları

Design of A Novel Device Measuring Testicular Consistency, Size and Temperature and Classification Algorithm Analysis of Data Compared to Urologist Examinations

Yazarlar:

Mehmet Çağrı Soylu | Oğuz Ekmekçioğlu

Yayıncı:

Erciyes University

Ana Başlıklar:

Biyomedikal Tanı

Dergi:

Enginoscope Vol.1 Issue 1, pp.60-75

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001342121

pISSN:

3062-2360

Infertility

Heat stress

Testicles Consistency

Machine LearningKısırlık

Isı Stresi

Testis Kıvamı

Makine Öğrenimi

Sayı

Makale detayları

Yazarlar: Mehmet Çağrı Soylu | Oğuz Ekmekçioğlu

Yayıncı: Erciyes University

Ana Başlıklar: Biyomedikal Tanı

Dergi: Enginoscope Vol.1 Issue 1, pp.60-75

Belge Tipi: Makale

Yayın Tarihi: 1/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001342121

pISSN: 3062-2360

Sayı

Yazarlar:

Mehmet Çağrı Soylu | Oğuz Ekmekçioğlu

Yayıncı:

Erciyes University

Ana Başlıklar:

Biyomedikal Tanı

Dergi:

Enginoscope Vol.1 Issue 1, pp.60-75

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001342121

pISSN:

3062-2360