Predicting mental health treatment outcomes using latent growth mixture models and machine learning in a real-world clinical setting.

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作者： Lee,Lancashire ^[1] ; Steven,Lancaster ^[2] ; David,Linkh ^[2] ; Anthony,Hassan ^[2] ; Magali,Haas ^[3] ; Allyson,Gage ^[3]

作者单位： Cohen Veterans Bioscience, New York, NY, USA. Electronic address: lee.lancashire@cohenbio.org. ^[1] Cohen Veterans Network, Stamford, CT, USA. ^[2] Cohen Veterans Bioscience, New York, NY, USA. ^[3]

关键词 Depression Latent class analysis PTSD

主题词人类(Humans);中年人(Middle Aged);女(雌)性(Female);成年人(Adult);男(雄)性(Male);老年人(Aged);青年人(Young Adult);青少年(Adolescent);回顾性研究(Retrospective Studies);老年人, 80以上(Aged, 80 and over);模型, 统计学(Models, Statistical);抑郁(Depression);治疗结果(Treatment Outcome)

DOI 10.1016/j.jpsychires.2024.12.007

PMID 39689556

发布时间 2025-01-20

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Journal of psychiatric research

2025年181卷

509-516页

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Predicting mental health treatment outcomes using latent growth mixture models and machine learning in a real-world clinical setting.

Journal of psychiatric research

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Journal of psychiatric research

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Predicting mental health treatment outcomes using latent growth mixture models and machine learning in a real-world clinical setting.

Journal of psychiatric research

相似文献

Journal of psychiatric research

相关期刊

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