MIMIC-IV-Note: Deidentified free-text clinical notes

The advent of large, open access text databases has driven advances in state-
of-the-art model performance in natural language processing (NLP). The
relatively limited amount of clinical data available for NLP has been cited as
a significant barrier to the field's progress. Here we describe MIMIC-IV-Note:
a collection of deidentified free-text clinical notes for patients included in
the MIMIC-IV clinical database. MIMIC-IV-Note contains 357,289 deidentified
discharge summaries from 161,403 patients admitted to the hospital and
emergency department at the Beth Israel Deaconess Medical Center in Boston,
MA, USA. The database also contains 2,471,881 deidentified radiology reports
for 256,400 patients. All notes have had protected health information removed
in accordance with the Health Insurance Portability and Accountability Act
(HIPAA) Safe Harbor provision. All notes are linkable to MIMIC-IV providing
important context to the clinical data therein. The database is intended to
stimulate research in clinical natural language processing and associated
areas.

大型开放获取文本数据库的问世，推动了自然语言处理（Natural Language Processing, NLP）领域前沿模型性能的提升。当前可用于自然语言处理的临床数据相对有限，这已被视为制约该领域发展的重大障碍。本研究介绍了MIMIC-IV-Note数据集：一款收录了MIMIC-IV临床数据库纳入患者的去标识化自由文本临床笔记集合。MIMIC-IV-Note包含来自美国马萨诸塞州波士顿贝斯以色列女执事医疗中心（Beth Israel Deaconess Medical Center）住院及急诊就诊的161403名患者的357289份去标识化出院小结，同时还收录了256400名患者的2471881份去标识化放射科报告。所有笔记均已按照《健康保险流通与责任法案》（Health Insurance Portability and Accountability Act, HIPAA）的安全港条款移除了受保护健康信息。所有笔记均可与MIMIC-IV数据库关联，为其中的临床数据提供重要背景信息。该数据集旨在推动临床自然语言处理及相关领域的研究发展。