Leverage real world evidences in oncology

We help medical professionals to structure and store patient's data using artificial intelligence. We streamline the use of RWE.

NLP Medical

Generate evidences

Gimli will help you streamline your real world data efficiently and transform it into real-world evidence.

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Privacy by default

Patients privacy is a major concern in healthcare, not for Gimli. Deploy pseudonymization of all your documents to protect patients privacy.

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Oncology focus

Data experts and oncologists collaborate to empower our AI and get relevant results for both clinicians and industrial partners.

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Scalability

Our platform will decrease the cost of all the analysis to be expended at a fair price for hospitals and healthcare industries.

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Easily deployable

We can easily adapt our system to work with all your clients and partners. Gimli can be your pocket partner for your medical data structuration needs.

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Interactive visualization

We provide all our clients and their partners with a powerful dashboard to manipulate their data and help them spread use of these beyond siloes.

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Not a black box

Our algorithms do not give results without an explanation! Audit trails and quality assessment are keys to our product.

Build for cancer specialists

The more we know about cancer, the more specific it becomes. That is why the study of cancer requires specific lexical granularity that we care about.

The problem

Data is stored unstructured in the EMR

Electronic medical records (EMR) contain raw data, in all medical reports stored in your HIS. This data is not easily retrievable. It takes considerable time for professionals to get this information. It is often incomplete and contains mistakes. It is not cost-effective, and not used as much as it could.

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How we solve it

We extract data from the EMR

We use Natural Language Processing (NLP) to help you structure your data directly from all your EMR, before storing it in your data warehouse.

We use international standards such as FHIR or OMOP so your data can be easily used for :

  • Large cohortes studies
  • Partnerships with pharmaceutical companies
  • More acurate billing
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Expertise

Specificity in oncology

We are a team composed of experts in data interoperability and oncology. We focus our value proposal on oncology, to help improve medical research in that field. Our vision is to significantly improve the research capabilities of oncology teams.

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They trust us

We have joined the Paris Saclay Cancer Cluster!

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The Gimlis

The Gimlis

Let's discuss NLP and real world data?