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论文ICLR 2026 Poster2026 年clinical prediction

从病历到诊断对话:面向精神共病的临床扎根方法与数据集

ICLR 2026 Poster accepted paper at ICLR 2026. Psychiatric comorbidity is clinically significant yet challenging due to the complexity of multiple co-occurring disorders. To address this, we develop a novel approach integrating synthetic patient electronic medical record (EMR) construction and multi-agent diagnostic dialogue generation. We create 502 synthetic EMRs for common comorbid conditions using a pipeline that ensures clinical relevance and diversity. Our multi-agent framework transfers the clinical interview protocol into a hierarchical state machine and context tree, supporting over 130 diagnostic states while maintaining clinical standards.

论文默认配图 - 医学影像计算

论文详情

英文标题
From Medical Records to Diagnostic Dialogues: A Clinical-Grounded Approach and Dataset for Psychiatric Comorbidity
作者
Tianxi Wan, Jiaming Luo, Siyuan Chen, Kunyao Lan, chenjianhua, Haiyang Geng, Mengyue Wu
期刊/会议
ICLR 2026 Poster
发表年份
2026 年
研究方向
clinical prediction