Application of artificial neural networks in dementia and alzheimer's diagnosis Demans ve Alzheimer TeGhisinde Yapay Sinir Aglarinin Uygulanmasi

Altug Yigit, Zerrin Isik

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Diagnosis in the early phases of many diseases makes it possible to treat the disease and affects the treatment process positively. This is especially important for diseases like Alzheimer in the field of neurology. The use of a computerized support system, which can autonomously perform the diagnostic process by the expert in this process, saves time and helps to reduce the most human errors. In this study, machine learning models with the ability to diagnose dementia and Alzheimer's disease were developed by predicting the Clinical Dementia Rating (CDR) value. Artificial Neural Networks (ANN), Logistic Regression (LR), k-nearest neighbors (KNN), and Decision Tree (DT) classifiers were applied to compare the classification performances. The Open Access Series of Imaging Studies (OASIS) longitudinal and cross-sectional datasets have been used to train models. As a result of the tests, best performance of the detection and identification of Alzheimer's disease has been shown by LR and YSA models.
Original languageEnglish
Title of host publication26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-4
ISBN (Electronic)9781538615010
DOIs
Publication statusPublished - 5 Jul 2018
Externally publishedYes
Event26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 - Izmir, Turkey
Duration: 2 May 20185 May 2018

Conference

Conference26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
Country/TerritoryTurkey
CityIzmir
Period2/05/185/05/18

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