Application of machine learning in predicting aggressive behaviors from hospitalized patients with schizophrenia
Bibliographic Data
| ID | 15518976 |
|---|---|
| Authors | Nuo Cheng (0000-0002-4748-4554, Zhengzhou University), Meihao Guo (0000-0003-4311-5206, Xinxiang Medical University), Fang Yan (0000-0002-4292-7328, Xinxiang Medical University), Zhengjun Guo (Xinxiang Medical University), Jun Meng (0000-0001-9716-1051, Xinxiang Medical University), Kui Ning (Henan Psychiatric Hospital), Yanping Zhang (0000-0001-7602-4453, Zhengzhou University), Zitian Duan (Xinxiang Medical University), Yong Han (0000-0002-3297-2782, Henan Psychiatric Hospital, corresponding author), Changhong Wang (0000-0001-7578-4856, Henan Psychiatric Hospital, corresponding author) |
| Year | 2023 |
| Volume | 14 |
| Pages | 1016586-1016586 |
| Publication date | 2023-03-20 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Psychiatry (JOURNAL) |
| Journal identifiers | ISSN: 1664-0640 • E-ISSN: 1664-0640 |
| Publisher | Frontiers Media (PUBLISHER • CH) |
| DOI | 10.3389/fpsyt.2023.1016586 |
| PMID | 37020730 |
| OpenAlex | W4327977685 |
| Language | EN |
| Citations received | 2 |
| References cited | 41 |
Machine learning models can fairly predict aggressive behaviors in hospitalized patients with schizophrenia, among which Random Forest has the best predictive effect and has some value in clinical application
Psychiatry · Schizophrenia (object-oriented programming · Clinical Psychology · Medicine · Mental Health Treatment and Access · Personality Disorders and Psychopathology · Psychology · Psychopathy, Forensic Psychiatry, Sexual Offending
Machine Learning Approaches for Clinical Psychology and Psychiatry
Human Aggression
Retrospective Study on the Influencing Factors and Prediction of Hospitalization Expenses for Chronic Renal Failure in China Based on Random Forest and Lasso Regression
The Prediction and Influential Factors of Violence in Male Schizophrenia Patients With Machine Learning Algorithms
| Unique citing works | 2 |
|---|---|
| Citations per year | 2 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 2 |