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ACL2026顶会

SOAPTriage: SOAP-Guided Multi-View Clinical Text Modeling Framework for Automated ESI Prediction

Enming Wang, Jianlei Wang, Xueping Peng, Hongjiao Guan, Yinglong Wang, Sibo Wei, Jianbin Guo, Ruifeng Xu, Wenpeng Lu

2026年份

摘要

Emergency departments (ED) rely on the Emergency Severity Index (ESI) to assess patient acuity and prioritize care, a process that is largely driven by clinical triage text. Despite recent progress in automated ESI prediction, two fundamental challenges remain: the scarcity of high-quality triage text data due to privacy and regulatory constraints and the lack of a clinically grounded triage framework capable of explicitly capturing the multidimensional structure of triage reasoning. To address these challenges, we draw inspiration from the clinically grounded SOAP paradigm, in which SOAP refers to Subjective, Objective, Assessment, and Plan and captures four complementary aspects of clinical reasoning. Building on this paradigm, we propose SOAPTriage, a SOAPguided multi-view clinical text modeling framework for automated ESI prediction. To mitigate data scarcity, SOAPTriage introduces a Clinical Note Augmentation (CNA) module that generates natural-language triage notes from structured ED records, resulting in 15,393 augmented clinical notes derived from a realworld dataset. To incorporate clinical structure, SOAPTriage employs a SOAP-Guided Encoding (SGE) module that models patient conditions from four complementary SOAP perspectives, together with an adaptive SOAP-Aware Aggregation and Inference (SAAI) module that performs multi-view reasoning to infer ESI levels. Extensive experiments show that SOAPTriage consistently outperforms strong prompting-based, multi-agent, and encoderbased baselines, demonstrating the effectiveness of SOAP-guided multi-view clinical text modeling for automated emergency triage. 1 * Equal contribution † Corresponding author 1 Our code and datasets can be found at https://github. com/xiaoyaoiii/SOAPTriage . Gap (i): Severe scarcity of highquality triage data. Structured ED Records Real-World Clinical Notes LLM-Generated Clinical Notes 15,393 Clinical Triage Notes Gap (ii): Lack of a clinically grounded triage framework. SOAP Clinical Theory Mid-Depth Embeddings Aggregation & Inference Reliable ESI Prediction Figure 1: Overview of SOAPTriage. The framework tackles triage data scarcity by generating clinical notes from structured records and real-world notes. It also addresses the lack of a clinically grounded triage framework by incorporating SOAP-guided reasoning, extracting multi-view representations, and aggregating them to infer reliable ESI predictions.

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