SPaDe: A Synonym-based Pain-level Detection Tool for Osteoarthritis

被引:2
作者
Chen, Yuhao [1 ]
Shu, Boqun [1 ]
Moattari, Mojtaba [1 ]
Zulkernine, Farhana [1 ]
Queenan, John [2 ]
Barber, David [2 ]
机构
[1] Queens Univ, Sch Comp, Kingston, ON, Canada
[2] Queens Univ, Dept Family Med, Kingston, ON, Canada
来源
2023 IEEE INTERNATIONAL CONFERENCE ON DIGITAL HEALTH, ICDH | 2023年
关键词
pain severity; osteoarthritis; primary healthcare; unstructured data; clustering;
D O I
10.1109/ICDH60066.2023.00026
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Osteoarthritis (OA) is a progressive chronic joint disease resulting in a breakdown of articular cartilage and bone when damaged joint tissues are not able to normally repair themselves. Over 300 million adults around the world suffer from symptomatic OA. The aim of this pilot research project is to understand the pain severity for OA and apply Information Extraction, Natural Language Processing and Machine Learning techniques to patients' primary care electronic medical records and physicians' chart notes and identify patients suffering from moderate-to-severe pain due to osteoarthritis. Pain level is explained using a variety of words in the chart notes and poses a difficult challenge for pain categorization only based on the words. We propose a pain level detection pipeline that integrates a synonym-based pain-level detection algorithm and unsupervised pain level detector. The results demonstrate the potential of our approach to identify patients with moderate to severe pain.
引用
收藏
页码:118 / 120
页数:3
相关论文
共 19 条
[1]  
[Anonymous], 2011, The impact of arthritis in Canada: Today and over the next 30 years
[2]  
Birtwhistle Richard, 2015, CMAJ Open, V3, pE270, DOI [10.9778/cmajo.20150018, 10.9778/cmajo.20150018]
[3]  
Canadian Primary Care Sentinel Surveillance Network (CPCSSN), 2021, About us
[4]  
Hartigan J. A., 1979, Applied Statistics, V28, P100, DOI 10.2307/2346830
[5]   Osteoarthritis [J].
Hunter, David J. ;
Bierma-Zeinstra, Sita .
LANCET, 2019, 393 (10182) :1745-1759
[6]   Diagnosing PTSD Using Electronic Medical Records from Canadian Primary Care Data [J].
Kaczmarek, Emily ;
Salgo, Alexander ;
Zafari, Hasan ;
Kosowan, Leanne ;
Singer, Alexander ;
Zulkernine, Farhana .
2019 6TH INTERNATIONAL CONFERENCE ON NETWORKING, SYSTEMS AND SECURITY (NSYSS 2019), 2019, :23-29
[7]  
Loper Edward., 2002, Proceedings of the ACL-02 Workshop on Effective tools and methodologies for teaching natural language processing and computational linguistics, V1, P63, DOI [DOI 10.3115/1225403.1225421, 10.3115/1118108.1118117, DOI 10.3115/1118108.1118117, 10.3115/1225403.1225421]
[8]  
McMaster University Family Medicine, 2021, OSCAR EMR.
[9]  
Pennington Jeffrey., 2014, Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, P1532, DOI DOI 10.3115/V1/D14-1162
[10]  
Pepin I., 2022, P 32 ANN INT C COMP