Automated Detection of Type of Scoliosis Surgery from Operative Notes Using Natural Language Processing

Elham Sagheb; Taghi Ramazania; Noelle Larson; Sunghwan Sohn; Hilal Maradit Kremers

doi:10.1109/ICHI54592.2022.00086

Automated Detection of Type of Scoliosis Surgery from Operative Notes Using Natural Language Processing

Elham Sagheb, Taghi Ramazania, Noelle Larson, Sunghwan Sohn, Hilal Maradit Kremers

Quantitative Health Sciences

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

Abstract

Scoliosis is an abnormal lateral curvature of the spine and managed surgically in severe cases. There is growing interest in comparing the effectiveness and safety of different surgical options. Yet, the type of surgical procedure is not readily available in a structured format in large databases but resides in the free text of the operative notes, hindering comparative effectiveness studies. In this study, we implemented a high-performance natural language processing (NLP) algorithm to classify 3 types of scoliosis surgery from the free text of operative notes.

Original language	English (US)
Title of host publication	Proceedings - 2022 IEEE 10th International Conference on Healthcare Informatics, ICHI 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	497-498
Number of pages	2
ISBN (Electronic)	9781665468459
DOIs	https://doi.org/10.1109/ICHI54592.2022.00086
State	Published - 2022
Event	10th IEEE International Conference on Healthcare Informatics, ICHI 2022 - Rochester, United States Duration: Jun 11 2022 → Jun 14 2022

Publication series

Name	Proceedings - 2022 IEEE 10th International Conference on Healthcare Informatics, ICHI 2022

Conference

Conference	10th IEEE International Conference on Healthcare Informatics, ICHI 2022
Country/Territory	United States
City	Rochester
Period	6/11/22 → 6/14/22

Keywords

Scoliosis
fusion
growing rod
natural language processing
non-fusion

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Information Systems and Management
Safety, Risk, Reliability and Quality
Health Informatics

Access to Document

10.1109/ICHI54592.2022.00086

Cite this

Sagheb, E., Ramazania, T., Larson, N., Sohn, S., & Kremers, H. M. (2022). Automated Detection of Type of Scoliosis Surgery from Operative Notes Using Natural Language Processing. In Proceedings - 2022 IEEE 10th International Conference on Healthcare Informatics, ICHI 2022 (pp. 497-498). (Proceedings - 2022 IEEE 10th International Conference on Healthcare Informatics, ICHI 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICHI54592.2022.00086

Automated Detection of Type of Scoliosis Surgery from Operative Notes Using Natural Language Processing. / Sagheb, Elham; Ramazania, Taghi; Larson, Noelle et al.
Proceedings - 2022 IEEE 10th International Conference on Healthcare Informatics, ICHI 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 497-498 (Proceedings - 2022 IEEE 10th International Conference on Healthcare Informatics, ICHI 2022).

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

Sagheb, E, Ramazania, T, Larson, N, Sohn, S & Kremers, HM 2022, Automated Detection of Type of Scoliosis Surgery from Operative Notes Using Natural Language Processing. in Proceedings - 2022 IEEE 10th International Conference on Healthcare Informatics, ICHI 2022. Proceedings - 2022 IEEE 10th International Conference on Healthcare Informatics, ICHI 2022, Institute of Electrical and Electronics Engineers Inc., pp. 497-498, 10th IEEE International Conference on Healthcare Informatics, ICHI 2022, Rochester, United States, 6/11/22. https://doi.org/10.1109/ICHI54592.2022.00086

Sagheb E, Ramazania T, Larson N, Sohn S , Kremers HM. Automated Detection of Type of Scoliosis Surgery from Operative Notes Using Natural Language Processing. In Proceedings - 2022 IEEE 10th International Conference on Healthcare Informatics, ICHI 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 497-498. (Proceedings - 2022 IEEE 10th International Conference on Healthcare Informatics, ICHI 2022). doi: 10.1109/ICHI54592.2022.00086

Sagheb, Elham ; Ramazania, Taghi ; Larson, Noelle et al. / Automated Detection of Type of Scoliosis Surgery from Operative Notes Using Natural Language Processing. Proceedings - 2022 IEEE 10th International Conference on Healthcare Informatics, ICHI 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 497-498 (Proceedings - 2022 IEEE 10th International Conference on Healthcare Informatics, ICHI 2022).

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title = "Automated Detection of Type of Scoliosis Surgery from Operative Notes Using Natural Language Processing",

abstract = "Scoliosis is an abnormal lateral curvature of the spine and managed surgically in severe cases. There is growing interest in comparing the effectiveness and safety of different surgical options. Yet, the type of surgical procedure is not readily available in a structured format in large databases but resides in the free text of the operative notes, hindering comparative effectiveness studies. In this study, we implemented a high-performance natural language processing (NLP) algorithm to classify 3 types of scoliosis surgery from the free text of operative notes.",

keywords = "Scoliosis, fusion, growing rod, natural language processing, non-fusion",

author = "Elham Sagheb and Taghi Ramazania and Noelle Larson and Sunghwan Sohn and Kremers, {Hilal Maradit}",

note = "Funding Information: Funding by following grants R01AR073147, P30AR7631. Publisher Copyright: {\textcopyright} 2022 IEEE.; 10th IEEE International Conference on Healthcare Informatics, ICHI 2022 ; Conference date: 11-06-2022 Through 14-06-2022",

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AB - Scoliosis is an abnormal lateral curvature of the spine and managed surgically in severe cases. There is growing interest in comparing the effectiveness and safety of different surgical options. Yet, the type of surgical procedure is not readily available in a structured format in large databases but resides in the free text of the operative notes, hindering comparative effectiveness studies. In this study, we implemented a high-performance natural language processing (NLP) algorithm to classify 3 types of scoliosis surgery from the free text of operative notes.

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Automated Detection of Type of Scoliosis Surgery from Operative Notes Using Natural Language Processing

Abstract

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Keywords

ASJC Scopus subject areas

Access to Document

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