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ibis.ai delivers advanced clinical language understanding, empowering healthcare institutions to act on the valuable information locked away in unstructured medical data.
Request your DEMO nowICD-10 coding is essential in the administrative processes of hospitals in many countries. We are working with Belgian hospitals to streamline the ICD-10 coding for the obligatory MZG registration.
Learn moreIn the context of migrating to next generation electronic health record systems, hospitals are looking to add value from the new possibilities offered by SNOMED CT based functionality.
Learn moreOur collaborative annotation tool allows efficient annotation of patient records with the relevant SNOMED CT concepts.
We provide a range of models and tools that can be combined to streamline the ICD-10/MZG coding environment.
Our approach is tailored to be easily usable and acceptable by healthcare professionals.
Our data-driven Clinical Language Understanding models learn from real-life examples. The system learns how the users work, not vice versa.
The initial system is a starting point. The AI models learn from further interactions with healthcare professionals, creating a positive feedback loop.
We focus on interpretable AI, where users can easily understand the AI suggestions and validate or correct based on the presented evidence.
Get to know us.
Our Clinical Language Understanding technology is at the core of the solutions we
build for and together with customers. A modular, container-based architecture
gives us the flexibility to adapt to different needs.
Flexibility also means flexibility in deployment. That's why we offer
on-site as well as cloud based deployment solutions. That way, healthcare institutions
can be in control of their own data.
Over the years, we have worked on multiple projects (e.g. adverse event detection)
and services (e.g. pseudonymization and anonymization). But the following are the
projects that have grown into real products:
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