BioNLP Workshop 2023 Shared Task 1A: Problem List Summarization

Automatically summarizing patients' main problems from the daily care notes in
the electronic health record can help mitigate information and cognitive
overload for clinicians and provide augmented intelligence via computerized
diagnostic decision support at the bedside. The task of Problem List
Summarization aims to generate a list of diagnoses and problems in a patient's
daily care plan using input from the provider's progress notes during
hospitalization.

This task aims to promote NLP model development for downstream applications in
diagnostic decision support systems that could improve efficiency and reduce
diagnostic errors in hospital care. The task contains 768 hospital daily
progress notes and 2783 diagnoses in the training set, and a new set of 237
daily progress notes are recently annotated as the test set. The annotation
methods and annotation quality have previously been reported.

The dataset supports a more complex summarization task to generate a list of
relevant diagnoses/problems given the information in the Subjective,
Objective, and Assessment sections of the note. Only diagnoses/problems that
are available in the progress note were labeled for the task.

从电子健康记录（Electronic Health Record, EHR）中的日常护理笔记自动提炼患者核心问题摘要，可帮助临床医师缓解信息与认知过载，并通过床边计算机化诊断决策支持系统提供增强智能。问题列表摘要（Problem List Summarization）任务旨在基于住院期间医护人员撰写的病程记录输入，生成患者日常护理计划中的诊断与问题清单。
本任务旨在推动自然语言处理（Natural Language Processing, NLP）模型面向诊断决策支持系统的下游应用开发，以提升医院诊疗效率并降低诊断失误率。该任务的训练集包含768份医院日常病程记录与2783条诊断条目，近期新增标注了237份日常病程记录作为测试集。标注方法与标注质量此前已有公开报道。
本数据集可支撑更复杂的摘要生成任务：基于病程记录的主观（Subjective）、客观（Objective）与评估（Assessment）章节信息，生成相关诊断/问题清单。本任务仅对病程记录中出现的诊断/问题进行标注。

搜集汇总

背景与挑战

背景概述

该数据集是BioNLP Workshop 2023共享任务1A的问题列表总结数据集，旨在从电子健康记录中自动总结患者的主要诊断和问题。数据包含768个训练笔记和237个测试笔记，来源于MIMIC-III的SOAP格式进展笔记，使用ROUGE-L作为评估指标，支持临床决策支持系统的NLP模型开发。