Imagine if hospitals had a smart digital assistant that could read thousands of discharge papers in different languages and instantly spot where care could be improved. It's like having a flight recorder for healthcare that ensures every patient gets the same high standard of treatment. The system also uses voice assistants to let patients easily report how they are feeling after leaving the hospital.
Hospitals struggle to monitor stroke care quality because discharge reports are written in different languages and often contain missing data, making large-scale auditing manual and inefficient.
An AI-driven platform featuring NLP for report ingestion, two voice assistants for patients and physicians, and a semantic Knowledge Graph for data normalization.
If you are a medical software provider dealing with fragmented patient data across different languages — this project developed NLP and semantic models that automate the ingestion of hospital reports. This allows for the creation of a standardized European Stroke Hospital Discharge Report Exchange Format to improve data reuse.
If you are a private hospital group dealing with inconsistent quality of care and manual auditing — this project developed AI voice assistants and a registry to monitor care quality. This ensures a level of quality control similar to commercial aviation for hospitalizations.
If you are an AI health startup dealing with the difficulty of cleaning messy medical records — this project developed a Knowledge Graph and AI to impute missing data from reports. This provides a foundation for building a European Open Stroke Data Platform.
Based on available project data, no specific pricing or commercial cost model is mentioned; however, the project received an EU contribution of EUR 7,702,741 for development.
Yes, the project aims for global deployment to solidify a leadership position in quality improvement, building on a registry already used by 74 countries worldwide.
Based on available project data, the project focuses on creating an 'Open Stroke Data Platform' and a 'standard European Stroke Hospital Discharge Report Exchange Format', suggesting a move toward open standards.
The project uses NLP to automate the ingestion of reports in different languages and specifically includes deliverables for localized versions in 2 additional EU languages.
The consortium is developing a legal and ethical toolbox to ensure compliance with all current and proposed Union legislation regarding health data.
The consortium is highly diversified with 22 partners across 13 countries, showing strong European integration. With a 27% industry ratio (6 companies, including 3 SMEs), there is a significant commercial interest in the output, balanced by 9 universities and 2 research centers to ensure scientific validity.
Contact USTAV ZDRAVOTNICKYCH INFORMACI A STATISTIKY CESKE REPUBLIKY in the Czech Republic
Contact us to explore licensing opportunities for the AI voice assistants or the semantic data repositories.
