From
Dr. Alberto Tozzi
Data requirements and infrastructure for artificial intelligence in healthcare
With Dr. Alberto Tozzi
Chapter 1 of 4
Data variety
Introduction and data variety challenges
Expert statements on this page
No expert statements were drawn from this page.
Host summaries · secondary, not cited in answers
Educational content from recorded physician discussions — not medical advice. Talk to your (or your child's) care team about your situation.
More from this expert
Dr. Alberto TozziPodcast
Ethical and regulatory implications of artificial intelligence in healthcare
Alberto Tozzi · 21 min · Published Oct 2026
Podcast
Using AI to Read Scientific Publications in Healthcare Research
Alberto Tozzi · 21 min · Published Oct 2026
Podcast
Evidence-based medicine and artificial intelligence in pediatric healthcare
Alberto Tozzi · 18 min · Published Oct 2026
Podcast
Digital Twins in Healthcare: Virtual Models for Personalized Medicine
Alberto Tozzi · 16 min · Published Oct 2026
Podcast
Le funzioni e gli usi dell'intelligenza artificiale per la salute
Alberto Tozzi · 14 min · Published Oct 2026
Podcast
Healthcare innovation requires cultural change beyond technology adoption
Alberto Tozzi · 21 min · Published Oct 2026
What the experts said
Traditional clinical repositories have limitations for supporting AI systems
Real-world data are significant for AI systems in healthcare
Electronic health records and clinical databases present infrastructure challenges for AI
Data silos exist where data are not shared between systems and cannot be retrieved in a usable way
Infrastructure problems are a fundamental barrier to AI implementation in healthcare
Federated learning is an informatics approach that allows AI algorithms to be trained across distributed datasets