Automated misspelling detection and correction in clinical free-text records

Aiman Khan Nazir; Usman Qamar; Iqra Zafar; Asma Shaheen; Alia Fatima; Bilal Maqbool

doi:10.1109/ICAIBD.2018.8396209

Automated misspelling detection and correction in clinical free-text records

Aiman Khan Nazir
, Usman Qamar
, Iqra Zafar
, Asma Shaheen
, Alia Fatima
, Bilal Maqbool

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

2 Scopus citations

Abstract

Correct record is important in all fields especially in the medical field. For correct medication, safety of patient and correct documentation accurate medical records are important. There is possibility that medical record can contain some misspelled words that can lead towards the wrong interpretation and wrong treatment of patients. So, it is necessary that the medical record must be correct for proper treatment and care of patients. Part of speech tagging is à mechanism that reads the text in documents and separates the different part of speech. Regular expression is a mechanism that is used to match the specific pattern of words in documents. A Methodology/spellchecker is proposed for automated misspelling detection and correction in medical free-text records for correction of misspelled terms. Proposed methodology is based on part of speech tagging and regular expression and is applied on all types of medical documents such as allergy entries, free-text medication order and clinical notes. Dictionary lookup is used for detection of misspelled words. Suffix and prefix based suggestion list is used for misspelled correction. Incorrect spellings from different medical documents are detected and corrected. A significant percentage of misspelling detection and correction is achieved.

Original language	English
Title of host publication	2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	277-280
Number of pages	4
ISBN (Electronic)	9781538669877
DOIs	https://doi.org/10.1109/ICAIBD.2018.8396209
State	Published - 25 Jun 2018
Externally published	Yes
Event	2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018 - Chengdu, China Duration: 26 May 2018 → 28 May 2018

Publication series

Name	2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018

Conference

Conference	2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018
Country/Territory	China
City	Chengdu
Period	26/05/18 → 28/05/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

Medical record
Misspelled correction
Misspelled detection
Misspelled words
Part of speech tagging
Regular expression
Spellchecker

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Information Systems and Management

Access to Document

10.1109/ICAIBD.2018.8396209

Cite this

Nazir, A. K., Qamar, U., Zafar, I., Shaheen, A., Fatima, A., & Maqbool, B. (2018). Automated misspelling detection and correction in clinical free-text records. In 2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018 (pp. 277-280). (2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAIBD.2018.8396209

Nazir, Aiman Khan ; Qamar, Usman ; Zafar, Iqra et al. / Automated misspelling detection and correction in clinical free-text records. 2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 277-280 (2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018).

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title = "Automated misspelling detection and correction in clinical free-text records",

abstract = "Correct record is important in all fields especially in the medical field. For correct medication, safety of patient and correct documentation accurate medical records are important. There is possibility that medical record can contain some misspelled words that can lead towards the wrong interpretation and wrong treatment of patients. So, it is necessary that the medical record must be correct for proper treatment and care of patients. Part of speech tagging is {\`a} mechanism that reads the text in documents and separates the different part of speech. Regular expression is a mechanism that is used to match the specific pattern of words in documents. A Methodology/spellchecker is proposed for automated misspelling detection and correction in medical free-text records for correction of misspelled terms. Proposed methodology is based on part of speech tagging and regular expression and is applied on all types of medical documents such as allergy entries, free-text medication order and clinical notes. Dictionary lookup is used for detection of misspelled words. Suffix and prefix based suggestion list is used for misspelled correction. Incorrect spellings from different medical documents are detected and corrected. A significant percentage of misspelling detection and correction is achieved.",

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author = "Nazir, \{Aiman Khan\} and Usman Qamar and Iqra Zafar and Asma Shaheen and Alia Fatima and Bilal Maqbool",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018 ; Conference date: 26-05-2018 Through 28-05-2018",

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Nazir, AK, Qamar, U, Zafar, I, Shaheen, A, Fatima, A & Maqbool, B 2018, Automated misspelling detection and correction in clinical free-text records. in 2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018. 2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018, Institute of Electrical and Electronics Engineers Inc., pp. 277-280, 2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018, Chengdu, China, 26/05/18. https://doi.org/10.1109/ICAIBD.2018.8396209

Automated misspelling detection and correction in clinical free-text records. / Nazir, Aiman Khan; Qamar, Usman; Zafar, Iqra et al.
2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 277-280 (2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018).

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

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AU - Maqbool, Bilal

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AB - Correct record is important in all fields especially in the medical field. For correct medication, safety of patient and correct documentation accurate medical records are important. There is possibility that medical record can contain some misspelled words that can lead towards the wrong interpretation and wrong treatment of patients. So, it is necessary that the medical record must be correct for proper treatment and care of patients. Part of speech tagging is à mechanism that reads the text in documents and separates the different part of speech. Regular expression is a mechanism that is used to match the specific pattern of words in documents. A Methodology/spellchecker is proposed for automated misspelling detection and correction in medical free-text records for correction of misspelled terms. Proposed methodology is based on part of speech tagging and regular expression and is applied on all types of medical documents such as allergy entries, free-text medication order and clinical notes. Dictionary lookup is used for detection of misspelled words. Suffix and prefix based suggestion list is used for misspelled correction. Incorrect spellings from different medical documents are detected and corrected. A significant percentage of misspelling detection and correction is achieved.

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BT - 2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 26 May 2018 through 28 May 2018

ER -

Nazir AK, Qamar U, Zafar I, Shaheen A, Fatima A, Maqbool B. Automated misspelling detection and correction in clinical free-text records. In 2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 277-280. (2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018). doi: 10.1109/ICAIBD.2018.8396209

Automated misspelling detection and correction in clinical free-text records

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this