Year 2019, Volume 22 , Issue , Pages 19 - 25 2019-11-29

USING DEEP LEARNING ALGORITHM TO DIAGNOSE PARKINSON DISEASE WITH HIGH ACCURACY
PARKİNSON HASTALIĞINI YÜKSEK DOĞRULUKLA TESPİT ETMEK İÇİN DERİN ÖĞRENME ALGORİTMASININ KULLANIMI

FAHRIYE GEMCI [1] , TURGAY IBRIKCI [2]


Early diagnosis of Parkinson's disease, which causes vital and permanent damage to both motor and non-motor symptoms, is very important to prevent further deterioration of the patient condition. In the present study, Parkinson's Disease data set from UCI repository is classified using deep learning architecture. The deep learning architecture in the study is a feed-forward neural network (FFNN) which is builded by Keras of Python. The architecture in the study composes of an input layer, two hidden layers and softmax function with ReLu (Rectified Linear Units) as an output layer. The deep learning architecture solves binary classification problem since PD data set has two classes. In order to classify the PD data set, many tests were performed by splitting the test and train data in different ratios. The PD data set classification was succeeded with 100% accuracy using deep learning algorithm splitting in %20 of the data as the test and the remaining as train data in epoch 30.

Hem motor hem de motor dışı semptomlarda hayati ve kalıcı hasara neden olan Parkinson hastalığının erken teşhisi, hasta durumunun daha da kötüleşmesini önlemek için çok önemlidir. Bu çalışmada, UCI deposundan alınan Parkinson Hastalığı verileri derin öğrenme mimarisi kullanılarak sınıflandırılmıştır. Çalışmadaki derin öğrenme mimarisi, Python Keras  tarafından oluşturulan ileri beslemeli bir sinir ağıdır (FFNN). Çalışmadaki mimari, bir girdi katmanı, iki gizli katman ve softmax fonksiyonunu ReLu (Rectified Linear Units) ile bir çıkış katmanı olarak oluşturulmaktadır. Derin öğrenme mimarisi, PD veri seti iki sınıfa sahip olduğundan dolayı, ikili veri sınıflandırma problemini çözer. PD veri setini sınıflandırmak için test ve eğitim verisi farklı oranlarda bölünerek birçok test yapıldı. PD veri seti sınıflandırması, % 20'sinde test ve kalan veri eğitim verisi olmak üzere, derin öğrenme algoritması kullanılarak % 100 doğrulukta başarılı oldu.

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Primary Language en
Subjects Computer Science, Information System
Journal Section Research Articles
Authors

Orcid: 0000-0003-0961-5266
Author: FAHRIYE GEMCI (Primary Author)
Institution: Kahramanmaras Sutcu Imam University
Country: Turkey


Orcid: 0000-0003-1321-2523
Author: TURGAY IBRIKCI
Institution: Cukurova University

Dates

Application Date : July 22, 2019
Acceptance Date : October 17, 2019
Publication Date : November 29, 2019

Bibtex @research article { ksujes594977, journal = {Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi}, issn = {}, eissn = {1309-1751}, address = {}, publisher = {Kahramanmaras Sutcu Imam University}, year = {2019}, volume = {22}, pages = {19 - 25}, doi = {}, title = {USING DEEP LEARNING ALGORITHM TO DIAGNOSE PARKINSON DISEASE WITH HIGH ACCURACY}, key = {cite}, author = {GEMCI, FAHRIYE and IBRIKCI, TURGAY} }
APA GEMCI, F , IBRIKCI, T . (2019). USING DEEP LEARNING ALGORITHM TO DIAGNOSE PARKINSON DISEASE WITH HIGH ACCURACY. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi , 22 () , 19-25 . Retrieved from http://jes.ksu.edu.tr/en/issue/50210/594977
MLA GEMCI, F , IBRIKCI, T . "USING DEEP LEARNING ALGORITHM TO DIAGNOSE PARKINSON DISEASE WITH HIGH ACCURACY". Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 22 (2019 ): 19-25 <http://jes.ksu.edu.tr/en/issue/50210/594977>
Chicago GEMCI, F , IBRIKCI, T . "USING DEEP LEARNING ALGORITHM TO DIAGNOSE PARKINSON DISEASE WITH HIGH ACCURACY". Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 22 (2019 ): 19-25
RIS TY - JOUR T1 - USING DEEP LEARNING ALGORITHM TO DIAGNOSE PARKINSON DISEASE WITH HIGH ACCURACY AU - FAHRIYE GEMCI , TURGAY IBRIKCI Y1 - 2019 PY - 2019 N1 - DO - T2 - Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi JF - Journal JO - JOR SP - 19 EP - 25 VL - 22 IS - SN - -1309-1751 M3 - UR - Y2 - 2019 ER -
EndNote %0 Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi USING DEEP LEARNING ALGORITHM TO DIAGNOSE PARKINSON DISEASE WITH HIGH ACCURACY %A FAHRIYE GEMCI , TURGAY IBRIKCI %T USING DEEP LEARNING ALGORITHM TO DIAGNOSE PARKINSON DISEASE WITH HIGH ACCURACY %D 2019 %J Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi %P -1309-1751 %V 22 %N %R %U
ISNAD GEMCI, FAHRIYE , IBRIKCI, TURGAY . "USING DEEP LEARNING ALGORITHM TO DIAGNOSE PARKINSON DISEASE WITH HIGH ACCURACY". Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 22 / (November 2019): 19-25 .
AMA GEMCI F , IBRIKCI T . USING DEEP LEARNING ALGORITHM TO DIAGNOSE PARKINSON DISEASE WITH HIGH ACCURACY. KSU J. Eng. Sci.. 2019; 22: 19-25.
Vancouver GEMCI F , IBRIKCI T . USING DEEP LEARNING ALGORITHM TO DIAGNOSE PARKINSON DISEASE WITH HIGH ACCURACY. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi. 2019; 22: 25-19.