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Journals / International Journal of Pure and Applied Sciences / 2026 / Volume: 11 Issue: 1

Detection of Alzheimer's Disease CNN Model Classification

Alzheimer Hastalığının Tespiti CNN Model Sınıflandırması

Ceren Gündüzalp0009-0006-5856-9146
Gökalp Tulum(TOPKAPI ÜNİVERSİTESİ,MÜHENDİSLİK FAKÜLTESİ,ELEKTRİK VE ELEKTRONİK MÜHENDİSLİĞİ DEPARTMANI)0000-0003-1906-0401
Tahsin Gündüzalp(SAĞLIK BİLİMLERİ ÜNİVERSİTESİ, İSTANBUL SANCAKTEPE ŞEHİR PROF. DR. İLHAN VARANK SAĞLIK UYGULAMA VE ARAŞTIRMA MERKEZİ, DAHİLİ TIP BİLİMLERİ BÖLÜMÜ, NÖROLOJİ ANABİLİM DALI)0009-0000-2394-5611
Pages
—
Publication Date
2025-06-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The CNN model used gave the accuracy value as 0.9102.These results show that by using the CNN model, data loss will be low and performance will be good.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The increasing use of computer-aided devices and systems in the health sector allows diseases to be diagnosed earlier and faster.
📊
Key Findings & Data:Developments in the evaluation of central nervous system and cognitive functions provide significant advantages, especially in the early diagnosis of neurodegenerative diseases such as Alzheimer's Disease.
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Conclusion & Impact:The CNN model used gave the accuracy value as 0.9102.These results show that by using the CNN model, data loss will be low and performance will be good.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Alzheimer’s Disease · CNN · Dementia

Abstract

The increasing use of computer-aided devices and systems in the health sector allows diseases to be diagnosed earlier and faster. Computer-aided systems and devices play a critical role in the diagnosis and imaging of neurological diseases in particular. Developments in the evaluation of central nervous system and cognitive functions provide significant advantages, especially in the early diagnosis of neurodegenerative diseases such as Alzheimer's Disease. The data used in the study were taken from the open source dataset called "Augmented Alzheimer MRI Dataset" on the Kaggle platform. The second folder was used in this data set. There are 33,894 images in total. In the study, Convolutional Neural Network (CNN) was used as a deep learning classifier model for Alzheimer's disease diagnostic analysis. Performance analysis was made. The CNN model used gave the accuracy value as 0.9102.These results show that by using the CNN model, data loss will be low and performance will be good.

Özet

Bilgisayar destekli cihaz ve sistemlerin sağlık sektöründe giderek artan kullanımı, hastalıkların daha erken ve daha hızlı teşhis edilmesine olanak sağlamaktadır. Bilgisayar destekli sistem ve cihazlar özellikle nörolojik hastalıkların tanı ve görüntülemesinde kritik bir rol oynamaktadır. Merkezi sinir sistemi ve bilişsel fonksiyonların değerlendirilmesindeki gelişmeler, özellikle Alzheimer Hastalığı gibi nörodejeneratif hastalıkların erken teşhisinde önemli avantajlar sağlamaktadır. Çalışmada kullanılan veriler Kaggle platformunda açık kaynaklı olarak bulunan “Augmented Alzheimer MRI Dataset” isimli veri setinden alınmıştır. Bu veri setinde ikinci klasör kullanılmıştır. Toplamda 33.894 adet görüntü bulunmaktadır. Çalışmada Alzheimer hastalığı teşhisi analizi için derin öğrenme sınıflandırıcı model olarak Convolutional Neural Network (CNN) kullanılmıştır. Performans analizi yapılmıştır. Kullanılan CNN model accuracy değerini 0.9102 olarak vermiştir. Bu sonuçlar, CNN modelin kullanılmasıyla veri kaybının düşük olacağını, performansın iyi olacağını göstermektedir.

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Cite This Article

Gündüzalp, C., Tulum, G., Gündüzalp, T. (2025). Detection of Alzheimer's Disease CNN Model Classification. International Journal of Pure and Applied Sciences, Volume: 11 Issue: 1. https://doi.org/10.29132/ijpas.1582591

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