Averbis Extraction Platform

The Averbis Extraction Platform (AEP) provides novel tools which enable the extraction of information from documents. The software identifies single information units possessing the highest relevance for the user and delivers answers to application-critical questions of the respective field by extracting relevant facts and revealing correlations.

Example personalized medicine

The treatment of serious diseases depends on a number of factors such as the clinical condition of a patient, demographic factors, treatment plans and genetic data. Die AEP is the basis for decision support systems with which relevant facts can be extracted from clinical data. It assists doctors in carrying out tailor-made therapies for patients and making prognoses on the success of the therapy.

Example patient safety

In the industrialized countries, more people die by adverse drug reaction (ADR) than in road traffic. With the AEP, information on medication can be extracted from medical reports and be referred to billing-relevant diagnoses. At the same time, contraindications and relevant existing conditions are identified and compared with medication information. With appropriate warnings, ADR could be prevented effectively.

Example Accounting of Medical Services

The AEP is able to extract billing-relevant information such as reason for admittance, auxiliary diagnoses, procedures and operations and relevant underlying diseases from patient files, thus saving doctors and controllers' valuable time and costs.

Example Libraries

The German National Library uses the AEP for the automatic classification and indexing of its digital internet publications. Here, relevant contents from free texts and literature data sets are automatically recognized and compared with the entries of a terminology. As a result, the thus generated, contextually standardized meta-information in the system can be stored for easy retrievability.

Example Company Data

In every company, great amounts of data accrue. Files are often scanned, for example, for better searchability and transformed into electronic Text using OCR (Optical Character Recognition). With the Averbis Extraction Platform, facts can be extracted systematically from these texts, e.g. personal names, geographic information, contract numbers or date information. These information units can on the one hand improve the search functionality and on the other hand it can be analyzed statistically.