CONSTRUCTION OF AN ANNOTATED MEDICAL TEXT CORPUS FOR INFORMATION EXTRACTION ON GENETIC DISEASES

The article presents an annotated corpus consisting of clinical texts in Russian, obtained by exomic sequencing. This corpus was developed to support the tasks of automatically identifying named objects and semantic relationships in relation to genes, mutations, hereditary diseases, phenotypic traits and their clinical significance. During the formation of the corpus, reports of actual clinical exomic sequencing were used, the data went through the stages of preliminary anonymization and text normalization. The labeling process used international standards and knowledge bases such as HGVS, OMIM, ClinVar, and HPO, and ensured consistency and accuracy of biomedical information. The corpus contains more than 25,000 biomedical objects and more than 6,000 semantic links, making it an important resource in the field of clinical genetics in terms of volume and content. The annotation was carried out manually with the participation of several experts, and the results were compared by cross-checking, and the level of agreement between the annotators was assessed using special indicators. The results obtained indicate the high quality and reliability of the case. The finished corpus makes it possible to effectively use natural language processing models in the field of medical genetics for teaching and evaluation, development of clinical decision support systems, and applied research for structuring genetic data.

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