Projects
2024: Testing AI and ML tools for structuring unstructured medical texts
Project duration
01.10.24 - 30.04.25
Project manager
Ahti Lohk
The goal of the project is to test the automatic structuring and validation of radiological texts by physicians during data entry, utilizing RDF, SNOMED, and ContSys where applicable. The project will explore and compare various AI technologies, including natural language processing (NLP), deep learning, and semantic analysis, to identify the most effective methods for formatting medical texts. The activities are divided into two main phases: 1) testing existing technologies, and 2) designing a prototype. If successful, the project is expected to reduce the time spent processing medical data, improve the accuracy of medical decision-making, and enhance semantic interoperability of data, ultimately reducing data analysis costs for healthcare and research institutions while increasing efficiency and improving data quality for both primary and secondary use.
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