Artificial intelligence already facilitates the everyday lives of many doctors. For example, when X-rays or MRI scans are taken, it detects disease patterns, helps with diagnoses and recommends treatments. However, AI-based solutions require thousands of concrete examples to learn and must be verified (validated) at the same time to be approved as a medical device. Data for the implementation of innovative AI products is often not big enough though and also not representative of the public. In addition, medical image data are highly sensitive patient data which are subject to the strict regulations of the GDPR and cannot be used without restriction.
This is exactly where the new “NeuroTest” project at Landshut University of Applied Sciences and deepc, overseen by Prof. Dr. Stefanie Remmele, is stepping in. The professor of Medical Technology research is researching how artificial patient data can be developed for use in AI models in medical imaging.
At the same time, we are working as project partners on an online platform to offer manufacturers of medical devices the opportunity to test their AI-based medical devices before applying for a license.
With the help of the development of methods to create synthetic reference data in combination with real patient data, which are constantly checked, added to, and compared at the same time using a standardized software platform, we expect clear progress in the standardization, application, and especially in the approval process for AI solutions in the field of imaging medical technology.
Our project is being funded by the Federal Ministry for Economic Affairs and Energy (Bundesministerium für Wirtschaft und Energie) with more than 400,000 euros, and deepc is contributing 225,000 euros from our own funds.
The Technische Universität Berlin and the Physikalisch-Technische Bundesanstalt, PTB are associated partners.
Find more insights here: https://www.haw-landshut.de/aktuelles/news/news-detailansicht/article/ki-anwendungen-in-der-medizin-sicherer-machen.html