logo averbis health discovery

Make Patients’ Lives Better With AI

Health Discovery is the text mining and machine learning platform for analyzing large amounts of patient data.

Health Discovery at a glance

Health Discovery is the healthcare text mining and machine learning platform for analyzing large amounts of patient data.

With Health Discovery, medical documents can be analyzed and searched for diagnoses, symptoms, prescriptions, special findings and other criteria. Heterogeneous patient data in a structured and unstructured form is harmonized, the content analyzed using text mining and natural language processing and made searchable using a uniform interface.

before text mining after text mining
Medical Understanding

Health Discovery understands the world of medical terminology, and that in different languages. We offer 50+ different NLP annotators that can be used out-of-the-box to extract various medical facts such as diagnoses, medication, laboratory values, etc.

AI-Applied Healthcare

We are leaders in applying the latest deep learning technology to healthcare. We combine it with the performance of the world’s most powerful text mining engine on the market – UIMA Ruta.

Making data usable

Health Discovery transforms unstructured “dirty” patient data into structured high-quality data. It maps all findings to semantic codes from medical terminology based on our curated terminology with millions of medical terms.

Get insigths

Health Discovery gives insights into large sets of patient records and identifies hidden relations in near-real time. It supports diagnosis and therapy, finds larger and better fitting patient selections and automates billing in hospitals.

Health Discovery enables meaningful predictions about diagnoses and therapy courses. Supported by natural language processing, patient cohorts can be compiled with just a few clicks – be it for feasibility studies and patient recruitment for clinical studies, for diagnostic support for rare diseases or to support medical coding specialists in medical billing.

Use Cases

The use of electronic patient data has a lasting impact on medical research. Routine medical data can be used to conduct retrospective observational and comparative studies. Much of the information needed in clinical research, such as diagnoses and symptoms, treatment history, functional values, etc., is often only available in free text. When this data is extracted from the texts and made available in a structured and semantically normalized form, many studies become possible in the first place, as many more clinical parameters are available, and more patients can be included in the studies.

With the introduction of Diagnoses Related Groups (DRGs), the coding and billing of medical and nursing services has changed significantly. The documentation and coding of medical and nursing services is complex and prone to errors. At the same time, this is a very repetitive and time-consuming process since many patients with the same diagnoses are coded in the same way several times a year.

With Health Discovery, missing codes and documentation gaps can be identified quickly and accurately. It enables an automated search for diagnoses and procedures and provides corresponding documents in the texts. You no longer have to manually process large amounts of clinical data and can concentrate on the essentials of your work.

Clinical studies are the key to medical progress. The use of NLP to determine patient populations is an important step towards obtaining more precise case numbers and more complete medical information about patients. Health Discovery enables the identification of larger patient cohorts, the refinement of inclusion and exclusion criteria, reduces the time and cost of recruitment, and thus increases the value of clinical trials significantly.

Medical errors are among the most common causes of death in Western countries. One of the reasons is the lack of relevant information at the right time. In the meantime, medical knowledge doubles every 100 days. Doctors can no longer keep all knowledge about diseases, therapies, drugs and their interactions in mind. The use of information technology is therefore indispensable in hospitals and medical practices. However, existing information systems are often isolated and health data cannot be systematically evaluated. A solution is provided by the use of artificial intelligence in combination with NLP (Natural Language Processing): large amounts of health-related information from different sources and formats can be linked and analyzed. This knowledge can be made available wherever medical decisions have to be made.

Adaption & Integration

Use as a stand-alone installation

  • Use the out of the box functionality and provide your own extensions
  • Load, analyze and inspect data via a graphical user interface
  • Export the results

Integration in your IT environment

  • use our integrated APIs
  • support your existing workflows
  • transfer results to local systems or BI tools
  • connect internal or external data sources

Build your own individual product

  • Add AI to your product
  • Get first class text mining and machine learning for your customers
  • Combine your and our expertise to create exponential value
Available on premise or in the cloud

What our Customers say

Prof. Dr. Hans-Ulrich Prokosch
Universitätsklinikum Erlangen
The complex process of anonymizing medical documents is significantly shortened by using Health Discovery. This enables large quantities of free medical texts to be made available for medical research.
Johannes Drepper
TMF e.V.

Averbis Health Discovery is a valuable contribution to data protection-compliant, networked medical research.

Prof. Dr. Kurt Marquardt
Universitätsklinikum Gießen und Marburg

Health Discovery is an effective tool to prepare textual information for research quickly and in accordance with data protection regulations.

Dr. Martin Richter
Klinische Landesregisterstelle des Krebsregisters Baden-Württemberg

Averbis Health Discovery helps us to slim down our work processes and reduce the burden on our documentalists. This saves us valuable time we can invest in other activities.

Marc Bliem
MetaIT GmbH
Managing Director

All hospitals should receive appropriate remuneration for their services. In order to adequately take into account coding-relevant information from free-text routine data such as doctors’ letters or laboratory reports, we use the AI software Health Discovery from Averbis. We are pleased that we were able to integrate the best text mining solution in Germany into our MetaKIS product. Our customers are thrilled.

Ready to go with just a few clicks!

In this video, we show you how you can configure Health Discovery as a text mining and machine learning platform and analyze large amounts of medical documents and patient data according to diagnoses, symptoms, prescriptions, special findings and other criteria in just a few minutes.

Would you like more information or a demo? We would be happy to present our products to you and create a demonstration based on your selected data.