Predictive utility of artificial intelligence on schizophrenia treatment outcomes: A systematic review and meta-analysis

This publication has 55 references indexed in Scilit:

• Machine learning techniques for the Schizophrenia diagnosis: a comprehensive review and future research directions
  Journal of Ambient Intelligence and Humanized Computing, 2023
• Advanced EEG-based learning approaches to predict schizophrenia: Promises and pitfalls
  Artificial Intelligence in Medicine, 2021
• Deep learning for the prediction of treatment response in depression
  Journal of Affective Disorders, 2021
• Risk‐of‐bias VISualization (robvis): An R package and Shiny web app for visualizing risk‐of‐bias assessments
  Research Synthesis Methods, 2020
• Schizophrenia—An Overview
  JAMA Psychiatry, 2020
• A network-based classification framework for predicting treatment response of schizophrenia patients
  Expert Systems with Applications, 2018
• Disrupted asymmetry of inter- and intra-hemispheric functional connectivity in patients with drug-naive, first-episode schizophrenia and their unaffected siblings
  EBioMedicine, 2018
• Brain morphometry of MR images for automated classification of first-episode schizophrenia
  Information Fusion, 2014
• A pilot study to determine whether machine learning methodologies using pre-treatment electroencephalography can predict the symptomatic response to clozapine therapy
  Clinical Neurophysiology, 2010
• Quantifying heterogeneity in a meta‐analysis
  Statistics in Medicine, 2002