Summary of Application Of Artificial Intelligence in Schizophrenia Rehabilitation Management: a Systematic Scoping Review, by Hongyi Yang et al.
Application of Artificial Intelligence in Schizophrenia Rehabilitation Management: A Systematic Scoping Review
by Hongyi Yang, Fangyuan Chang, Dian Zhu, Muroi Fumie, Zhao Liu
First submitted to arxiv on: 17 May 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The systematic review explores the current state and future prospects of artificial intelligence (AI) in schizophrenia rehabilitation management. It analyzed 61 studies published from 2012-2024, focusing on AI-related data types, feature engineering methods, algorithmic models, and evaluation metrics. The study categorizes AI applications into five key areas: symptom monitoring, medication management, risk management, functional training, and psychosocial support. Supervised machine learning techniques, particularly for symptom monitoring and relapse risk management, are the most prevalent approaches, leveraging structured data while incorporating interpretable algorithms. This review underscores the potential of AI in transforming long-term management strategies for schizophrenia, offering valuable insights into improving patients’ quality of life. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Artificial intelligence (AI) is being used to help people with schizophrenia manage their condition better. Researchers looked at 61 studies that used AI from 2012-2024. They found that AI can be very good at tracking symptoms and predicting when someone might have a relapse. This could help doctors give the right treatment at the right time. The study also shows that AI can help people with schizophrenia manage their medication and stay safe. It’s like having a personal assistant to help with daily tasks! Overall, this research is exciting because it suggests that AI could really improve people’s lives if used correctly. |
Keywords
* Artificial intelligence * Feature engineering * Machine learning * Supervised * Tracking
