@inproceedings{5013634ccae3451f95dd1f90f9e21807,
title = "Measuring Pain in Sickle Cell Disease using Clinical Text",
abstract = "Sickle Cell Disease (SCD) is a hereditary disorder of red blood cells in humans. Complications such as pain, stroke, and organ failure occur in SCD as malformed, sickled red blood cells passing through small blood vessels get trapped. Particularly, acute pain is known to be the primary symptom of SCD. The insidious and subjective nature of SCD pain leads to challenges in pain assessment among Medical Practitioners (MPs). Thus, accurate identification of markers of pain in patients with SCD is crucial for pain management. Classifying clinical notes of patients with SCD based on their pain level enables MPs to give appropriate treatment. We propose a binary classification model to predict pain relevance of clinical notes and a multiclass classification model to predict pain level. While our four binary machine learning (ML) classifiers are comparable in their performance, Decision Trees had the best performance for the multiclass classification task achieving 0.70 in F-measure. Our results show the potential clinical text analysis and machine learning offer to pain management in sickle cell patients.",
keywords = "Machine Learning, Pain Management, Sickle Cell Disease, Text Mining",
author = "Amanuel Alambo and Ryan Andrew and Sid Gollarahalli and Jacqueline Vaughn and Tanvi Banerjee and Krishnaprasad Thirunarayan and Daniel Abrams and Nirmish Shah",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 ; Conference date: 20-07-2020 Through 24-07-2020",
year = "2020",
month = jul,
doi = "10.1109/EMBC44109.2020.9175599",
language = "English (US)",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5838--5841",
booktitle = "42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society",
address = "United States",
}