{
  "id": 13186,
  "url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1760912",
  "title": "From mechanistic models to artificial intelligence: exploring the potential of digital twins in geriatric oncology",
  "summary": "This survey explores how machine learning and artificial intelligence (AI) can be integrated with mechanistic models to create more accurate, dynamic, predictive, and personalized representations of biological systems, commonly referred to as digital twins (DTs). Mechanistic models, such as pathway-based Boolean or differential equation frameworks, provide interpretable insights into biological processes; however, calibrating these models to represent individual variability across large, heterog",
  "authors": "Panagiotis Karampelesis",
  "category": "research",
  "topics": "biotech",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-23T00:00:00.000Z",
  "fetched_at": "2026-07-25T05:10:48.796Z",
  "source_slug": "x-frontiers-in-artificial-intelligence",
  "source_name": "Frontiers in Artificial Intelligence",
  "source_homepage": "https://www.frontiersin.org/journals/artificial-intelligence",
  "ethics_ai_record_url": "https://ethics.ai/record/13186",
  "original_url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1760912",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}