{
  "id": 6127,
  "url": "https://arxiv.org/abs/2604.08217v1",
  "title": "Co-design for Trustworthy AI: An Interpretable and Explainable Tool for Type 2 Diabetes Prediction Using Genomic Polygenic Risk Scores",
  "summary": "The polygenic risk scores (PRS) have emerged as an important methodology for quantifying genetic predisposition to complex traits and clinical disease. Significant progress has been made in applying PRS to conditions such as obesity, cancer, and type 2 diabetes (T2DM). Studies have demonstrated that PRS can effectively identify individuals at high risk, thereby enabling early screening, personalized treatment, and targeted interventions for diseases with a genetic predisposition. One current lim",
  "authors": "Ralf Beuthan, Megan Coffee, Heejin Kim, Na Yeon Kim, Pedro Kringen, Elisabeth Hildt et al.",
  "category": "research",
  "topics": "healthcare,transparency,biotech",
  "orgs": null,
  "regions": null,
  "published_at": "2026-04-09T13:14:34.000Z",
  "fetched_at": "2026-07-14T16:32:15.637Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/6127",
  "original_url": "https://arxiv.org/abs/2604.08217v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}