Automatic Spelling Detection and Correction in the Medical Domain: A Systematic Literature Review

  • Jésica López-HernándezEmail author
  • Ángela Almela
  • Rafael Valencia-García
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1124)


Automatic spelling correction is one of the most important problems in natural language processing. Its difficulty increases in medical corpora, due to the intrinsic particularities that have these texts. These features include the use of specific terminology, abbreviations, acronyms and the presence of writing errors. In this article we present a systematic review of the literature on automatic spelling detection and correction for the medical domain. There are many works on detection and automatic correction, but there is no review delving into the process of automatic correction in the medical domain. Therefore, we intend to synthesize all the existing information on this research topic and the types of studies that have been carried out to date. We present the main techniques and resources, and finally also the limitations and specific challenges. The results reflect the importance of compiling an exhaustive dictionary. In addition, the results show the ordinary use of distance algorithms of spelling and phonetic similarity, as well as with statistical techniques. The improvement of performance in recent years is especially relevant because of the use of context-based methods, such as linguistic models or neural embeddings.


Literature review Automatic spelling detection Automatic spelling correction Medical domain Spelling errors Misspellings 



This research was funded by the Spanish National Research Agency (AEI) and the European Regional Development Fund (FEDER/ERDF) through project KBS4FIA (TIN2016-76323-R). This research is also funded by the Ministry of Education of Spain through the National Program for University Teacher Training (FPU/Ayudas para la formación de profesorado universitario).


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Jésica López-Hernández
    • 1
    Email author
  • Ángela Almela
    • 2
  • Rafael Valencia-García
    • 1
  1. 1.Facultad de InformáticaUniversidad de MurciaMurciaSpain
  2. 2.Facultad de LetrasUniversidad de MurciaMurciaSpain

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