This review aims to systematically assess the current status and prospects of artificial intelligence (AI) in the rehabilitation management of patients with schizophrenia and their impact on the rehabilitation process. We selected 70 studies from 2012 to the present, focusing on application, technology categories, products, and data types of machine learning, deep learning, reinforcement learning, and other technologies in mental health interventions and management. The results indicate that AI can be widely used in symptom monitoring, relapse risk prediction, and rehabilitation treatment by analyzing ecological momentary assessment, behavioral, and speech data. This review further explores the potential challenges and future directions of emerging products, technologies, and analytical methods based on AI, such as social media analysis, serious games, and large language models in rehabilitation. In summary, this study systematically reviews the application status of AI in schizophrenia rehabilitation management and provides valuable insights and recommendations for future research paths.

翻译：本综述旨在系统评估人工智能（AI）在精神分裂症患者康复管理中的现状与前景及其对康复过程的影响。我们筛选了2012年至今的70项研究，重点关注机器学习、深度学习、强化学习等技术在心理健康干预与管理中的应用、技术类别、产品及数据类型。结果表明，AI可通过分析生态瞬时评估、行为及言语数据，广泛应用于症状监测、复发风险预测及康复治疗。本综述进一步探讨了基于AI的新兴产品、技术及分析方法（如社交媒体分析、严肃游戏及大语言模型）在康复中的潜在挑战与未来方向。综上，本研究系统回顾了AI在精神分裂症康复管理中的应用现状，并为未来研究路径提供了有价值的见解与建议。