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Yapay Sinir Ağları Kullanarak Topuk Kemiği Bohler Açısının Tahmin Edilmesi

Boehler’s Angle Estimations in Calcaneus Bone by Using Artificial Neural Networks

Journal Name:

  • Cumhuriyet Üniversitesi Fen Fakültesi Fen Bilimleri Dergisi

Publication Year:

  • 2015
DOI: 
http://dx.doi.org/10.17776/csj.56855

Key Words:

Keywords (Original Language):

Author NameUniversity of AuthorFaculty of Author
Abstract (2. Language): 
Boehler’s angle has a great importance in diagnosis and treatment of calcaneus bones fractures. In this study, Boehler’s angle was estimated by using artificial neural network method. This angle was obtained from 51 well-preserved calcaneus bones which was previously measured in anatomy laboratory at Cumhuriyet University. The data values for estimation belonging to these 51 different calcaneus bones are maximum anteroposterior length, maximum height, cuboidal facet height, body height and load arm length. By using this five different parameters, ANN estimation on Boehler’s angle was performed. It is clearly seen from the results that the method is capable for the estimation.
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Abstract (Original Language): 
Topuk kemiği kırıklarının teşhis ve tedavisinde, Bohler açısı büyük öneme sahiptir. Bu çalışmada, Bohler açısı, yapay sinir ağları metodu ile tahmin edilmiştir. Bu açı, daha önceden Cumhuriyet Üniversitesi anatomi laboratuvarlarında 51 tane iyi korunmuş topuk kemiğinden elde edilmiştir. Tahmine ait veriler, maksimum anteroposteriyor uzunluğu, maksimum yükseklik, kübital faset yüksekliği, vücut boyu ve yük kolu uzunluğudur. Bu 5 farklı parametre kullanılarak, Bohler açısı üzerine ANN tahminleri yapılmıştır. Açıkça görülmüştür ki, metod bu tahmin için elverişlidir.
FULL TEXT (PDF): 
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  • Turkish

REFERENCES

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Boehler’s Angle Estimations in Calcaneus Bone by Using Artificial Neural Networks
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