Smart Reporting to participate in AI Innovation Contest

A consortium led by Smart Reporting has been selected by the German Federal Ministry of Economics (BMWi) to participate in their AI Innovation Contest launched in January this year. Smart Reporting, the Munich Technical University (TUM), the Mannheim University Hospital (UMM) and Siemens Healthineers are now eligible to compete against other consortia for funding of up to € 10 million with their project idea “KID: Artificial Intelligence in Medical Diagnostics”.

The German Federal Government has set itself the goal of promoting digital transformation of the economy and the use of Artificial Intelligence (AI) is seen as a central building block for the success of future digital applications. With its AI strategy, the Federal Government underlines its claim to make Germany and Europe a leading location for the development and application of AI technologies. The BMWi has thus launched the AI Innovation Contest, intended to promote German industry, enable them to use AI and foster technology transfer to small and medium enterprises.

A total of more than 130 projects have been submitted to the original call, among which 35 have been chosen to enter the competition phase. Smart Reporting, TUM, UMM and Siemens Healthineers were selected by an independent expert panel to enter this competition with the project idea “KID: Artificial Intelligence in Medical Diagnostics”. KID aims to establish a competitive ecosystem for the development of AI-assisted medical diagnostics and decision support. The ecosystem will establish an infrastructure for the translation of innovative AI solutions from universities, spin-offs, SMEs and industry into the clinic, thus laying the foundation for the formation of an innovation hub and value network for the establishment of AI-driven assistance systems in medical diagnostics.

Expenses incurred during the competition phase will be covered by the BMWi and will amount to a total funding of up to € 700.000 for the consortium. The funding will be used to establish a research and development roadmap for the intended ecosystem. This includes the development of concepts for data protection and standardization, as well as validation, benchmarking, certification and marketing of diagnostic AI solutions.