通过数字表型来改善心理健康:将患者行为分组，以支持个性化决策。

Q3 Medicine

Recenti progressi in medicina Pub Date : 2025-10-01 DOI:10.1701/4573.45778

Joy Bordini, Rita Cosoli

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引用次数: 0

摘要

突破性的数字表型分析方法从智能手机数据中揭示了三种不同的行为模式，这可能会彻底改变个性化的心理健康护理。通过对77名用户的人工智能聚类，我们发现了“夜猫子”、“常规导向”和“永远连接”的行为类型，准确率达到90%以上。我们可解释的ML管道确定了目标干预的关键数字生物标志物，为临床医生提供精确精神病学的数据驱动见解。

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Migliorare l’assistenza per la salute mentale con la fenotipizzazione digitale: raggruppamento dei comportamentit dei pazienti per il supporto decisionale personalizzato.

Breakthrough digital phenotyping approach reveals three distinct behavioral patterns from smartphone data that could revolutionize personalized mental health care. Using AI clustering on 77 users, we discovered "Night Owls", "Routine-Oriented", and "Always-Connected" behavioral types with 90%+ accuracy. Our explainable ML pipeline identifies key digital biomarkers for targeted interventions, offering clinicians data-driven insights for precision psychiatry.

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来源期刊

Recenti progressi in medicina Medicine-Medicine (all)

CiteScore

0.90

自引率

0.00%

发文量

143

期刊介绍： Giunta ormai al sessantesimo anno, Recenti Progressi in Medicina continua a costituire un sicuro punto di riferimento ed uno strumento di lavoro fondamentale per l"ampliamento dell"orizzonte culturale del medico italiano. Recenti Progressi in Medicina è una rivista di medicina interna. Ciò significa il recupero di un"ottica globale e integrata, idonea ad evitare sia i particolarismi della informazione specialistica sia la frammentazione di quella generalista.