Artificial intelligence in medical technology – potential and challenges

Artificial intelligence is becoming a key driver of innovation in medical technology, opening up new possibilities in prevention, diagnosis, therapy, and patient care, and paving the way for personalized medicine. AI-supported systems improve image analysis, support clinical decisions, enable continuous monitoring, and increase the precision of medical technology applications through automation and robotic assistance. In addition, AI accelerates research, development, and production and increases efficiency throughout the entire product life cycle—from the concept phase to prototyping and manufacturing to application and post-market surveillance.

At the same time, the use of AI brings with it technical, regulatory, and ethical challenges. High demands on data quality, data protection, and IT security, questions of transparency and accountability, and complex approval processes—especially for learning systems—characterize current developments. In addition, AI is changing qualification requirements and making it necessary to build targeted expertise in the industry. In order to use the potential of AI responsibly and effectively, shared data rooms, clear standards, pre-competitive cooperation, and a constructive approach to digital transformation are required.

The session highlights key potential areas for AI in medical technology and presents approaches for overcoming current challenges. The aim is to discuss conditions and solutions that contribute to viewing AI more as an opportunity than a risk.

Please note: the lecture will be held in German.

Supported by VDE DGBMT