Leveraging Ontotext’s Eligibility Design Assistant for Effective Patient Population Selection
Combining highly normalized knowledge graphs with large language models for quick and reliable selection of clinical trial eligibility criteria
Making Sense of Text and Data
Combining highly normalized knowledge graphs with large language models for quick and reliable selection of clinical trial eligibility criteria
Ivelina Nikolova
Katerina Serafimova
Georgi Iliev
Todor PrimovRead about Ontotext’s methodology for building knowledge graphs coupled with an extensive experience working in Life Sciences, Pharma and Healthcare.
Ilian Uzunov
Todor PrimovRead about a more in-depth dive into the joint solution provided by Ontotext and metaphacts that detaildemonstrates how GraphDB and metaphactory work together through an example from clinical trial scoping.
Todor Primov
Sebastian SchmidtRead about the basics of the joint solution provided by Ontotext and metaphacts and how it can help you accelerate your knowledge graph journey.
Todor Primov
Sebastian SchmidtRead about our scientific literature monitoring solution for drug safety signaling, which utilizes the publicly available safety information in the form of knowledge graphs.
Todor PrimovLearn how Linked Data solutions for Healthcare break down the barriers of information silos and give a broad view of patients’ and research data.
Todor Primov