{
  "id": 3849,
  "url": "https://arxiv.org/abs/2605.24162v1",
  "title": "Knowledge Graph Modulated Deep Learning for Limited-Sample Clinical Data Analysis",
  "summary": "Biological systems are governed by structured molecular interactions, where pathways, regulatory circuits, and functional gene relationships shape cellular behavior and disease progression. Much of this knowledge is naturally represented as graphs. However, most biomedical AI models cannot directly use graph-encoded biological knowledge and instead require compressed low-dimensional representations, which can lose important structure and reduce performance, especially in limited-sample clinical ",
  "authors": "Yuwei Xue, Sakib Mostafa, James Zou, Joseph Liao, Maximilian Diehn, Ash A. Alizadeh et al.",
  "category": "research",
  "topics": "regulation,healthcare,biotech",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-22T19:33:04.000Z",
  "fetched_at": "2026-07-14T16:30:31.923Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/3849",
  "original_url": "https://arxiv.org/abs/2605.24162v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}