The World Health Organization (WHO) reports that 20 million people worldwide are affected by this mental disorder. Therefore, it is necessary to develop an automated model to diagnose patients that can help doctors to start medical treatment early. This research aims to compare machine learning algorithms in the classification of schizophrenia, a mental condition that is often difficult to diagnose, this research is expected to help improve accuracy in the schizophrenia diagnosis process. The research approach involves applying a Logistic Regression model trained with medical and psychological data from schizophrenia patients. The developed model was then tested to evaluate its accuracy in detecting schizophrenia. The accuracy result obtained using the Logistic Regression model was 93.6%.
Copyrights © 2023