Thesis

Diagnosis for Schizophrenia Patients in EEG Signals Using Multiple Optimizers in Convolutional Neural Network (CNN)

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Schizophrenia is a mental illness that makes it difficult for a person to think and behave
clearly. The clinical examination in determining schizophrenia may take a long time, around 12
months to 36 months, depending on the interval of protocols. EEG is one of the alternatives, a
neuroimaging technique that helps determining schizophrenia in patients. The method starts with
downloading dataset from Kaggle which consists of 81 patients but then filtered down to 30 patients.
The deep learning method in data preprocessing is called a Convolutional Neural Network (CNN). In
addition, six optimizers would be used to help analyze and make the convolutional neural network
model that has been made, which are Adam, Adadelta, Root Mean Square Propagation, Adagrad,
Stochastic Gradient Descent, and Adamax. Between these six optimizers, the result is chosen based
on the highest values of accuracy, sensitivity, specificity, precision, and F-measure, along with their
models of loss and accuracy. Based on the conducted experiment result, the optimizer with the
highest value was Root Mean Square Propagation, which has accuracy values of 0.8693, sensitivity
values of 0.66, precision values of 0.74, specificity values of 0.67, and an F-measurement of 0.7. The
conclusion is that Root Mean Square Propagation has the most suitable optimizer for the current
dataset in identifying patients who have schizophrenia. For future work, the dataset needs to be
added more to gain values for the parameters. Another method that could be used for the study is
using a hybrid of deep learning between a convolutional neural network with long short-term
memory.

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Availability

Detail Information

Series Title

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Call Number

BI 22-001

Publisher

i3L, Jakarta : i3L, Jakarta., 2022

Collation

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Language

English

ISBN/ISSN

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Classification

NONE

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Schizophrenia
EEG,
CNN
Optimizers
Deep Learning

Specific Detail Info

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Statement of Responsibility

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