This paper is in the following e-collection/theme issue:

Tools, Programs and Algorithms (356) Natural Language Processing (866) Electronic Health Records (1268)

Published on in Vol 3, No 3 (2015): Jul-Sep

Context-Sensitive Spelling Correction of Consumer-Generated Content on Health Care

Context-Sensitive Spelling Correction of Consumer-Generated Content on Health Care

Context-Sensitive Spelling Correction of Consumer-Generated Content on Health Care

Authors of this article:

Xiaofang Zhou1, 2 Author Orcid Image ;   An Zheng2 Author Orcid Image ;   Jiaheng Yin2, 3 Author Orcid Image ;   Rudan Chen2 Author Orcid Image ;   Xianyang Zhao2 Author Orcid Image ;   Wei Xu2 Author Orcid Image ;   Wenqing Cheng2 Author Orcid Image ;   Tian Xia2, 4 Author Orcid Image ;   Simon Lin5 Author Orcid Image
Article Authors Cited by (10) Tweetations (3) Metrics

Journals

  1. Sarker A, Gonzalez-Hernandez G. An unsupervised and customizable misspelling generator for mining noisy health-related text sources. Journal of Biomedical Informatics 2018;88:98 View
  2. Dirkson A, Verberne S, Sarker A, Kraaij W. Data-Driven Lexical Normalization for Medical Social Media. Multimodal Technologies and Interaction 2019;3(3):60 View
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  4. Sarker A, Jonathan W. LexExp: a system for automatically expanding concept lexicons for noisy biomedical texts. Bioinformatics 2021;37(16):2499 View
  5. Kim T, Han S, Kang M, Lee S, Kim J, Joo H, Sohn J. Similarity-Based Unsupervised Spelling Correction Using BioWordVec: Development and Usability Study of Bacterial Culture and Antimicrobial Susceptibility Reports. JMIR Medical Informatics 2021;9(2):e25530 View
  6. Hernández J, Molina F, Almela Á. Analysis of Context-Dependent Errors in the Medical Domain in Spanish: A Corpus-Based Study. Sage Open 2023;13(1) View
  7. Tetzlaff L, Heinrich A, Schadewitz R, Thomeczek C, Schrader T. Die Analyse des CIRSmedical.de mittels Natural Language Processing. Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen 2022;169:1 View
  8. Dashti S, Dashti S. Improving the quality of Persian clinical text with a novel spelling correction system. BMC Medical Informatics and Decision Making 2024;24(1) View

Books/Policy Documents

  1. López-Hernández J, Almela Á, Valencia-García R. Technologies and Innovation. View

Conference Proceedings

  1. Jiang W, Ye Z, Ou Z, Zhao R, Zheng J, Liu Y, Liu B, Li S, Yang Y, Zheng Y. Proceedings of the 31st ACM International Conference on Information & Knowledge Management. MCSCSet: A Specialist-annotated Dataset for Medical-domain Chinese Spelling Correction View