SynthMedic: Utilizing large language models for synthetic discharge summary generation, correction and validation

Georgi Grazhdanski, Vasil Vasilev, Sylvia Vassileva, Dimitar Taskov, Izabel Antova, Ivan Koychev, Svetla Boytcheva, SynthMedic: Utilizing large language models for synthetic discharge summary generation, correction and validation, Journal of Biomedical Informatics, Volume 170, October 2025, 104906

Ontotext Demo Days: Extracting the Knowledge in Your Content via Ontotext Metadata Studio

A talk by Borislav Ankov, Project Manager at Ontotext, presented at the Ontotext Demo Day in May 2022.

Borislav Ankov, Project manager at Ontotext, presents an introduction to Ontotext Metadata Studio (OMDS) – a new Ontotext product that helps organizations find out if they can automatically extract the knowledge locked within their valuable unstructured content.

This includes a walkthrough of some key OMDS features that enable:

semantic representation of any use case within the product;
establishing the Ground Truth for a set of documents;
evaluating any text analysis service against the Ground Truth baseline;
analyzing the results & unlocking insights.

Want more like this? The Ontotext Recommendations engine combines content and its semantic fingerprint to retrieve knowledge graph-driven recommendations. It is integrated with the Ontotext Metadata Studio tagging to power meaningful recommendations based on both semantic relevancy and recency.

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SynthMedic: Utilizing large language models for synthetic discharge summary generation, correction and validation

Want more like this? The Ontotext Recommendations engine combines content and its semantic fingerprint to retrieve knowledge graph-driven recommendations. It is integrated with the Ontotext Metadata Studio tagging to power meaningful recommendations based on both semantic relevancy and recency.

Want to chat more with us? Reach out and let's do it!