Neurocognition as a major predictor of 8-week response to antipsychotics for drug-naive first-episode schizophrenia using machine learning.

ABSTRACT: Cognitive impairments are generally observed in patients with schizophrenia. However, it is unclear whether neurocognitive dysfunction can predict the efficacy of antipsychotics for first-episode schizophrenia (FES). Machine learning methods provide a relatively unbiased approach when evaluating heterogeneous data, especially when building multifactor prediction models. This study conducted a secondary analysis based on the Chinese FES Trial (CNFEST), which was a 1-year study involving a randomized controlled trial for the first eight weeks followed by a 48-week open-label observation. The current study aimed to build a prediction model of eight-week antipsychotic response based on baseline clinical and demographic features. Six machine learning algorithms, including random forest, eXtreme

SUBMITTER: Wang X 

PROVIDER: S-EPMC12284124 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature