Ecosystem for Pathology Diagnostics with AI Assistance

01 / Data

The EMPAIA platform provides standardized access to data for the development and validation of AI algorithms as well as tools for the creation and use of data via a repository. 

02 / Services

EMPAIA offers a secure marketplace for services that support clinical diagnosis and research. The seamless integration into existing workflows is central to these efforts.

03 / Certification

Besides validation, the certification of algorithms for deployment as well as billing for diagnostic services play important roles. The platform will support the orchestration of developers, reference sites and certification mechanisms to provide solutions of assured high quality.




Pathology and AI

Artificial intelligence (AI) methods will revolutionize all areas of diagnostic medical imaging in the coming years. This applies to pathology in particular, where there are great opportunities and benefits from digitization. Moreover, AI can also support overcoming several major challenges that pathology is currently facing.


Complexity of case workup is also continuously increasing, in order to meet the requirements of targeted therapy and of immuno-oncology in particular. In addition to classical morphologic and microscopic interpretation, diagnoses are increasingly based on complex molecular information, such as from “omics” fields. Cancer screening programs are expanding and there is a growing shortage of specialists.


The aim of this project is the establishment of an ecosystem for image-based, AI-assisted, diagnostic services, using pathology as an example. By creating a standardized marketplace within a clearly defined legal framework, physicians will be able to routinely use validated and approved AI solutions.





EMPAIA Consortium

Project coordination:

Prof. Dr. Peter Hufnagl


Phone:  +49-30-4 50 53 61 40

Fax:       +49-30-4 50 53 69 10 


Charité - Universitätsmedizin Berlin

Institute of Pathology

Digital Pathology

Charitéplatz 1

10117 Berlin


Funded by: