Healthcare Analytics

Fraunhofer IAIS is your partner on the way to a more efficient future in the healthcare industry! With our advanced solutions in generative AI, foundation models and LLMs (Large Language Models), we are at the forefront of technology developed specifically for hospitals and pharmaceutical companies. Our accurate planning and evaluation of clinical trials through AI enables high precision and speed, while our AI-based physician letter generator and automated form filling simplify and speed up routine tasks.


The integration of generative AI into medical coding and documentation not only shows that these technologies have "arrived", but that they are already being used for many critical tasks. Our hybrid approaches, which include both on-premise and cloud solutions, offer flexible and secure ways to implement AI in your organization. With these innovations, we increase efficiency while reducing errors by automating and improving routine processes.


Find out more about your AI readiness with our special check for hospitals and clinics. Join the movement that has already convinced many customers through our GenAI Campus format. Take part in our Innovation Briefings to get a deep insight into the world of generative AI. Make the right choice for your institution and implement future-proof efficiency increase with Fraunhofer IAIS.

Portfolio of services

Our services include optimizing procedures within medical organizations, developing systems that help making decisions easier, analyzing medical data, evaluating study outcomes and structuring new approaches for physicians and patients. Our customers include medical facilities, pharmaceutical companies and manufacturers of medical devices.

Supporting clinical studies

Clinical studies are conducted in a controlled environment and their outcomes are evaluated for statistical purposes. Machine Learning methods are ideal for deriving answers from data material. They cannot only provide answers to questions but also discover patterns that have yet not been recognized.

We can either analyze clinical studies retrospectively (secondary analysis) or gather any information prospectively. In doing so we can develop new analytical procedures, such as for the study of chronic diseases related to the immune system.

Our partnership with the Fraunhofer ITMP makes this possible.

Text Mining for medical documents

A significant amount of information vitally important to routine medical procedures exists in the form of text documents. These documents can be wide ranging and can include specialized medical literature and study outcome publications as well as physician’s letters and medical reports.

We offer Text Mining solutions based on "Natural Language Understanding". It involves extracting the essential information from all of the relevant documents and making it available in a structured format.

Digitalization in medical facilities

The healthcare sector can benefit enormously from digitalization and the opportunities it creates for increased efficiency, quality and new ways of working.

We help you identify and unlock this potential. We also support you with the design and targeted implementation of a made-to-measure digitalization strategy.

Working together we can determine which procedures need to be digitalized and what specific application scenarios might look like.


KI.NRW flagship project


Using AI to treat patients better, relieve hospital staff and make medical processes more efficient – these are the goals of SmartHospital.NRW.


»Künstliche Intelligenz im Krankenhaus«


The use of AI in hospitals offers many potentials – but also challenges. Emergency care was examined for the white paper. It is written in German.

Innovations for the healthcare industry

Medical NLU.Campus

Work hand-in-hand with our scientists on your NLU solution for the healthcare sector.

Visualization of COVID-19 infection chains ...

... with "CorASiV" and "COPERIMOPlus". The new software supports health authorities in recording infection chains.


Optimized care of seriously injured persons

... through data-driven decision support using artificial intelligence.

A digital patient model

... for improved long-term treatment and care based on knowledge graphs.

Promoting activity among older people

... by analyzing lifestyle data through Machine Learning.

Early detection of Parkinson's disease

... through the use of voice technologies via smartphones and wearables.

Support for colon cancer therapy

... by selecting, preparing and planning the appropriate therapy with the "Electronic Patient Path".

Early diagnosis of subclinical arthritis

... by finding biomarkers through integrative data analysis.