Open AccessA Random Forest Model for Predicting Social Functional Improvement in Chinese Patients with Schizophrenia After 3 Months of Atypical Antipsychotic Monopharmacy: A Cohort Study
Author(s) -
Yange Li,
Lei Zhang,
Yan Zhang,
Wen Han,
Jingjing Huang,
Yifeng Shen,
Huafang Li
Publication year - 2021
Publication title -
neuropsychiatric disease and treatment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.819
H-Index - 67
eISSN - 1178-2021
pISSN - 1176-6328
DOI - 10.2147/ndt.s280757
Subject(s) - medicine , generalizability theory , schizophrenia (object oriented programming) , tolerability , psychiatry , antipsychotic , atypical antipsychotic , cohort , clinical psychology , adverse effect , psychology , developmental psychology
Impaired social functions contribute to the burden of schizophrenia patients and their families, but predictive tools of social functioning prognosis and specific factors are undefined in Chinese clinical practice. This article explores a machine learning tool to identify whether patients will achieve significant social functional improvement after 3 months of atypical antipsychotic monopharmacy and finds the defined risk factors using a multicenter clinical study.