Life sciences – Advancing personalized care in a regulated world
This track explores how you can accelerate medical innovation while ensuring compliance with AI tools, microfluidics and digital platforms.
Garbage in, garbage out: The importance of data quality for AI and how it can be improved
Learn what ‘high-quality’ data means for AI and explore best practices for continuous improvements and proactive data-gathering strategies.
Digital innovation in 2024: what’s in, what’s out
From AI, custom platforms and clean tech, to AR and data-driven insights, take a look at the trends that we think are set to define this year’s innovation landscape.
Designing energy-efficient deep learning algorithms
When reducing Ultra-Fine Particles becomes a matter of health
AI-enabled sustainability through process optimization
AI and machine learning enable sustainable production thanks to process optimization. Find out how in this InnoDays webinar.
The added value of blockchain in ports & logistics
Blockchain is more than a buzzword or hype, even without considering Bitcoin. The potential of the underlying technology is truly immense.
Data monetization for digital health
Data monetization is a quickly emerging trend in the digital MedTech sector due to increasing competition, new technologies & changing policies.
Focusing patient treatment on prevention & personalization
MedTech companies can transform patient treatment by focusing on prevention and personalization instead of illnesses.
End-to-end optimization of supply chain management
Calculating low-cost routing solutions is very complex. Nevertheless, algebraic modeling can optimize the supply chain substantially.
Federated learning: embedding privacy in the learning algorithm
Distributed learning raises critical issues in data privacy, security & access rights. Find out why & how federated learning can solve them.