Pycaret for the evaluation of classification methods in order to set up a decision making system for the early diagnosis of schizophrenia by EEG-Reference-Cited by-同舟云学术

Pycaret for the evaluation of classification methods in order to set up a decision making system for the early diagnosis of schizophrenia by EEG

Published:2022-10 Issue: Volume: Page:
ISSN:
Container-title:2022 16th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)
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Author:

Temgoua Nanfack Pelagie Flore¹,Tagne Fute Elie²,Abiama Ele Patrice³

Affiliation:

1. University of Buea, Ministry of Scientific Research and Innovation,National Committee for Development of Technologies,Department of Computer Engineering,Yaounde,Cameroon

2. University of Buea, University of Dschang,Department of Computer Engineering, Department of Mathematics and Computer Science,Buea,Cameroon

3. Institute of Geological and Mining Research Ministry of Scientific Research and Innovation,Yaounde,Cameroon

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10089803/10089992/10090088.pdf?arnumber=10090088

Reference28 articles.

1. Automatic Diagnosis of Schizophrenia in EEG Signals Using Functional Connectivity Features and CNN-LSTM Model

2. A Computerized Method for Automatic Detection of Schizophrenia Using EEG Signals

3. Study of Metrics that Could be Considered as Inputs to an Intelligent System for Diagnosing Schizophrenia based on an Electroencephalogram (EEG);temgoua nanfack;EJERS,2020

4. Graph-based analysis of brain connectivity in schizophrenia

5. Automated detection of schizophrenia using nonlinear signal processing methods

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