{
  "id": 9277307,
  "title": "Diagnostic Labels and Measurement Timing Drive Systematic Inconsistency in ADNI Neuroimaging Data",
  "url": "https://urgent.news/2026/09/22/diagnostic-labels-and-measurement-timing-drive-systematic",
  "topic": "health",
  "section": "Health & Medicine",
  "published": "2026-09-22T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.09.16.752036v1?rss=1"
  },
  "original_language": "en",
  "account": null,
  "summary": "The Alzheimer's Disease Neuroimaging Initiative (ADNI) is widely used to train machine learning models for Alzheimer's disease, yet whether it provides consistent ground truth for predictive modeling has not been systematically tested. In this paper, we showed that ADNI contains three interacting sources of bias with direct implications for machine learning: (a) diagnostic label inconsistency,…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}