Identifying Mentions of Life Stressors in Clinical Notes

被引：0

作者：

Datar, Shreya ^{[1
]}

Lindemann, Elizabeth A. ^{[2
]}

Silverman, Greg ^{[2
]}

McEwan, Reed ^{[3
]}

Finzel, Raymond ^{[4
]}

Kotlyar, Michael ^{[4
]}

Melton, Genevieve B. ^{[5
]}

Pakhomov, Serguei V. S. ^{[6
]}

机构：

[1] Univ Minnesota, Coll Pharm, Dept Comp Sci, Minneapolis, MN 55455 USA

[2] Univ Minnesota, Dept Surg, Minneapolis, MN USA

[3] Univ Minnesota, Acad Hlth Ctr Off Informat Syst, Minneapolis, MN USA

[4] Univ Minnesota, Coll Pharm, Minneapolis, MN USA

[5] Univ Minnesota, Dept Surg, Inst Hlth Informat, Minneapolis, MN USA

[6] Univ Minnesota, Coll Pharm, Inst Hlth Informat, Minneapolis, MN USA

来源：

2021 IEEE 9TH INTERNATIONAL CONFERENCE ON HEALTHCARE INFORMATICS (ICHI 2021) | 2021年

基金：

美国医疗保健研究与质量局;

关键词：

knowledge representation; text mining; informatics; medical information systems; ELECTRONIC HEALTH RECORDS; SOCIAL DETERMINANTS; INTERVENTIONS; INVENTORY; SYSTEM; TEXT;

D O I：

10.1109/ICHI52183.2021.00033

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The impact of social determinants on individual health has increasingly been recognized. In this study, we aimed to understand the representation of stressful life events occurring in clinical reports generated outside of mental health specialties. We present a conceptual schema for the representation of stressful events and associated linguistic attributes within free-text clinical notes. We also evaluated existing "off-the-shelf" clinical Natural Language Processing (NLP) systems for the detection of stress related concepts in clinical notes. We found that mentions of stressful events are prevalent even in non-mental health specialties, and that capturing details of stress mentions is challenging. Our results further indicate that existing NLP systems can serve as a reasonable starting point for developing models trained specifically for extracting stress associated information from clinical narratives.

引用

页码：153 / 160

页数：8

共 46 条

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