Automated Spelling Correction for Clinical Text Mining in Russian

04/10/2020 ∙ by Ksenia Balabaeva, et al. ∙ 0

The main goal of this paper is to develop a spell checker module for clinical text in Russian. The described approach combines string distance measure algorithms with technics of machine learning embedding methods. Our overall precision is 0.86, lexical precision - 0.975 and error precision is 0.74. We develop spell checker as a part of medical text mining tool regarding the problems of misspelling, negation, experiencer and temporality detection.

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