  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.
