Project objective:
Develop a solution for automatic processing of medical texts, identification and structuring of clinical terms using SNOMED CT codes and FHIR standard.
Work plan:
1. Clinical term identification
- Preprocessing of Estonian medical texts
- Application of machine learning/language models for term identification from text
- Structuring of identified terms for further processing
2. Standardization and coding
- Linking identified terms with SNOMED CT codes
- Semantic matching of data with standardized ontologies
- Converting results to FHIR format
Demo solution and expected outputs:
- Practical demonstration solution for complete workflow
- Working system for automatic identification of clinical terms from Estonian texts
- Structured output of terms linked with SNOMED CT codes
- Standard data presentation in FHIR format for further use
Keywords: medical texts, SNOMED CT, FHIR, language processing, clinical terms, automatic annotation, structured data
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