ArticleWorld journal of psychiatry2024
Identification of male schizophrenia patients using brain morphology based on machine learning algorithms.
Article in World journal of psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundSchizophrenia is a severe psychiatric disease, and its prevalence is higher. However, diagnosis of early-stage schizophrenia is still considered a challenging task.
aimTo employ brain morphological features and machine learning method to differentiate male individuals with schizophrenia from healthy controls.
methodsThe least absolute shrinkage and selection operator and
resultsA total of 8 important features with significant differences between groups were considered as input features for the establishment of classification models based on the four machine learning algorithms. Compared to other machine learning algorithms, RF yielded better performance in the discrimination of male schizophrenic individuals from healthy controls, with an AUC of 0.886.
conclusionOur research suggests that brain morphological features can be used to improve the early diagnosis of schizophrenia in male patients.
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