Explainable NLP Model for Predicting Patient Admissions at Emergency Department Using Triage Notes

Emilien Arnaud; Mahmoud Elbattah; Pedro A. Moreno-Sanchez; Gilles Dequen; Daniel Aiham Ghazali

doi:10.1109/BigData59044.2023.10386753

Explainable NLP Model for Predicting Patient Admissions at Emergency Department Using Triage Notes

Emilien Arnaud
, Mahmoud Elbattah
, Pedro A. Moreno-Sanchez
, Gilles Dequen
, Daniel Aiham Ghazali

Emergency Department
Amiens-Picardy University
Université de Picardie Jules Verne
College of Arts
University of the West of England
Tampere University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Citations (Scopus)

Abstract

Explainable Artificial Intelligence (XAI) has the potential to revolutionize healthcare by providing more transparent, trustworthy, and understandable predictions made by AI models. To this end, the present study aims to develop an explainable NLP model for predicting patient admissions to the emergency department based on triage notes. We utilize transformer models to leverage the extensive textual data captured in triage notes, while also delivering interpretable results by using the LIME approach. The results show that the proposed model provides satisfactory accuracy along with an interpretable understanding of the factors contributing to patient admission. In general, this work highlights the potential of NLP in improving patient care and decision-making in emergency medicine.

Original language	English
Title of host publication	Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023
Editors	Jingrui He, Themis Palpanas, Xiaohua Hu, Alfredo Cuzzocrea, Dejing Dou, Dominik Slezak, Wei Wang, Aleksandra Gruca, Jerry Chun-Wei Lin, Rakesh Agrawal
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4843-4847
Number of pages	5
ISBN (Electronic)	9798350324457
DOIs	https://doi.org/10.1109/BigData59044.2023.10386753
Publication status	Published - 2023
Externally published	Yes
Event	2023 IEEE International Conference on Big Data, BigData 2023 - Sorrento, Italy Duration: 15 Dec 2023 → 18 Dec 2023

Publication series

Name	Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023

Conference

Conference	2023 IEEE International Conference on Big Data, BigData 2023
Country/Territory	Italy
City	Sorrento
Period	15/12/23 → 18/12/23

Keywords

BERT
Emergency Department
Explainable Artificial Intelligence (XAI)
Natural Language Processing
Transformers
Triage

Access to Document

10.1109/BigData59044.2023.10386753

Cite this

Arnaud, E., Elbattah, M., Moreno-Sanchez, P. A., Dequen, G., & Ghazali, D. A. (2023). Explainable NLP Model for Predicting Patient Admissions at Emergency Department Using Triage Notes. In J. He, T. Palpanas, X. Hu, A. Cuzzocrea, D. Dou, D. Slezak, W. Wang, A. Gruca, J. C.-W. Lin, & R. Agrawal (Eds.), Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023 (pp. 4843-4847). (Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData59044.2023.10386753

Arnaud, Emilien ; Elbattah, Mahmoud ; Moreno-Sanchez, Pedro A. et al. / Explainable NLP Model for Predicting Patient Admissions at Emergency Department Using Triage Notes. Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023. editor / Jingrui He ; Themis Palpanas ; Xiaohua Hu ; Alfredo Cuzzocrea ; Dejing Dou ; Dominik Slezak ; Wei Wang ; Aleksandra Gruca ; Jerry Chun-Wei Lin ; Rakesh Agrawal. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 4843-4847 (Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023).

@inproceedings{fcaf5759373643a092fbe748810555c3,

title = "Explainable NLP Model for Predicting Patient Admissions at Emergency Department Using Triage Notes",

abstract = "Explainable Artificial Intelligence (XAI) has the potential to revolutionize healthcare by providing more transparent, trustworthy, and understandable predictions made by AI models. To this end, the present study aims to develop an explainable NLP model for predicting patient admissions to the emergency department based on triage notes. We utilize transformer models to leverage the extensive textual data captured in triage notes, while also delivering interpretable results by using the LIME approach. The results show that the proposed model provides satisfactory accuracy along with an interpretable understanding of the factors contributing to patient admission. In general, this work highlights the potential of NLP in improving patient care and decision-making in emergency medicine.",

keywords = "BERT, Emergency Department, Explainable Artificial Intelligence (XAI), Natural Language Processing, Transformers, Triage",

author = "Emilien Arnaud and Mahmoud Elbattah and Moreno-Sanchez, \{Pedro A.\} and Gilles Dequen and Ghazali, \{Daniel Aiham\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Big Data, BigData 2023 ; Conference date: 15-12-2023 Through 18-12-2023",

year = "2023",

doi = "10.1109/BigData59044.2023.10386753",

language = "English",

series = "Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "4843--4847",

editor = "Jingrui He and Themis Palpanas and Xiaohua Hu and Alfredo Cuzzocrea and Dejing Dou and Dominik Slezak and Wei Wang and Aleksandra Gruca and Lin, \{Jerry Chun-Wei\} and Rakesh Agrawal",

booktitle = "Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023",

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}

Arnaud, E, Elbattah, M, Moreno-Sanchez, PA, Dequen, G & Ghazali, DA 2023, Explainable NLP Model for Predicting Patient Admissions at Emergency Department Using Triage Notes. in J He, T Palpanas, X Hu, A Cuzzocrea, D Dou, D Slezak, W Wang, A Gruca, JC-W Lin & R Agrawal (eds), Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023. Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023, Institute of Electrical and Electronics Engineers Inc., pp. 4843-4847, 2023 IEEE International Conference on Big Data, BigData 2023, Sorrento, Italy, 15/12/23. https://doi.org/10.1109/BigData59044.2023.10386753

Explainable NLP Model for Predicting Patient Admissions at Emergency Department Using Triage Notes. / Arnaud, Emilien; Elbattah, Mahmoud; Moreno-Sanchez, Pedro A. et al.
Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023. ed. / Jingrui He; Themis Palpanas; Xiaohua Hu; Alfredo Cuzzocrea; Dejing Dou; Dominik Slezak; Wei Wang; Aleksandra Gruca; Jerry Chun-Wei Lin; Rakesh Agrawal. Institute of Electrical and Electronics Engineers Inc., 2023. p. 4843-4847 (Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Explainable NLP Model for Predicting Patient Admissions at Emergency Department Using Triage Notes

AU - Arnaud, Emilien

AU - Elbattah, Mahmoud

AU - Moreno-Sanchez, Pedro A.

AU - Dequen, Gilles

AU - Ghazali, Daniel Aiham

PY - 2023

Y1 - 2023

N2 - Explainable Artificial Intelligence (XAI) has the potential to revolutionize healthcare by providing more transparent, trustworthy, and understandable predictions made by AI models. To this end, the present study aims to develop an explainable NLP model for predicting patient admissions to the emergency department based on triage notes. We utilize transformer models to leverage the extensive textual data captured in triage notes, while also delivering interpretable results by using the LIME approach. The results show that the proposed model provides satisfactory accuracy along with an interpretable understanding of the factors contributing to patient admission. In general, this work highlights the potential of NLP in improving patient care and decision-making in emergency medicine.

AB - Explainable Artificial Intelligence (XAI) has the potential to revolutionize healthcare by providing more transparent, trustworthy, and understandable predictions made by AI models. To this end, the present study aims to develop an explainable NLP model for predicting patient admissions to the emergency department based on triage notes. We utilize transformer models to leverage the extensive textual data captured in triage notes, while also delivering interpretable results by using the LIME approach. The results show that the proposed model provides satisfactory accuracy along with an interpretable understanding of the factors contributing to patient admission. In general, this work highlights the potential of NLP in improving patient care and decision-making in emergency medicine.

KW - BERT

KW - Emergency Department

KW - Explainable Artificial Intelligence (XAI)

KW - Natural Language Processing

KW - Transformers

KW - Triage

UR - https://www.scopus.com/pages/publications/85184981614

U2 - 10.1109/BigData59044.2023.10386753

DO - 10.1109/BigData59044.2023.10386753

M3 - Conference contribution

AN - SCOPUS:85184981614

T3 - Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023

SP - 4843

EP - 4847

BT - Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023

A2 - He, Jingrui

A2 - Palpanas, Themis

A2 - Hu, Xiaohua

A2 - Cuzzocrea, Alfredo

A2 - Dou, Dejing

A2 - Slezak, Dominik

A2 - Wang, Wei

A2 - Gruca, Aleksandra

A2 - Lin, Jerry Chun-Wei

A2 - Agrawal, Rakesh

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Conference on Big Data, BigData 2023

Y2 - 15 December 2023 through 18 December 2023

ER -

Arnaud E, Elbattah M, Moreno-Sanchez PA, Dequen G, Ghazali DA. Explainable NLP Model for Predicting Patient Admissions at Emergency Department Using Triage Notes. In He J, Palpanas T, Hu X, Cuzzocrea A, Dou D, Slezak D, Wang W, Gruca A, Lin JCW, Agrawal R, editors, Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 4843-4847. (Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023). doi: 10.1109/BigData59044.2023.10386753

Explainable NLP Model for Predicting Patient Admissions at Emergency Department Using Triage Notes

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