arXiv cs.AI· Sudeshna Jana, Siddhartha Laha, Manjira Sinha, Tirthankar Dasgupta, Pabitra Mitra·· 12 小时前AI 评分26
临床叙事能否揭示慢性病住院患者的新发心理健康风险？
Beyond Physical Illness: Can Clinical Narratives Reveal Emerging Mental Health Risks in Chronically Ill Patients?
AI 导读
研究基于 MIMIC-III 构建约 4,000 名患者的弱监督队列，用出院小结中的心理健康证据标注，检验能否从纵向临床叙事推断慢性病患者的潜在心理健康风险。团队提出分层状态空间框架，从逐日临床叙事中提取心理健康表征并建模其时间演化，用于住院全程风险估计。初步结果显示该表征提升了二分类风险预测，且风险组与无风险组呈现不同的模型推导风险轨迹。
正文
Abstract:Mental-health risks such as depression, dementia, and suicidal ideation can emerge during hospitalization among chronically ill patients and may worsen without timely recognition and intervention. However, most existing mental health studies focus on patients with established psychiatric conditions rather than patients hospitalized primarily for physical illness. In this work, we investigate whether latent mental-health risk in chronically ill patients can be inferred from longitudinal clinical narratives. We construct a weakly supervised cohort around 4,000 patients from MIMIC-III using mental-health evidence extracted from discharge summaries. A hierarchical state-space framework derives mental-health representations from day-wise clinical narratives and models their temporal evolution for risk estimation throughout hospitalization. Preliminary results demonstrate improved binary risk prediction using the proposed representations and show distinct model derived risk trajectories between risk and no-risk cohorts, providing a foundation for studying emerging mental-health risks in chronically ill patients.
| Subjects: | Artificial Intelligence (cs.AI); Machine Learning (cs.LG) |
| Cite as: | arXiv:2610.35761 [cs.AI] |
| (or arXiv:2610.35761v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.35761 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Sudeshna Jana [view email]
[v1]
Mon, 26 Oct 2026 17:06:33 UTC (144 KB)
来源：arXiv cs.AI · arxiv.org