{
  "abstract": "In 2026, artificial intelligence (AI) systems are deployed at scale to support clinical decision-making. Algorithms detect cardiac arrhythmias from ECGs, classify skin lesions from photographs and predict deterioration in critically ill patients. These tools are valuable. However, they share a critical vulnerability: they are trained on labelled datasets where the labels (the diagnoses) derive from clinical assessments recorded in electronic health records (EHRs). The fundamental assumption is that these clinical diagnoses represent the ground truth. This assumption merits examination.",
  "authors": [
    {
      "affiliations": [
        "Department of Forensic Pathology, Southern Medical University, Guangzhou, China"
      ],
      "name": "Qi Wang"
    }
  ],
  "title": "AI mirage: medical algorithms and the vanishing autopsy",
  "uid": "1993f970-2be5-5f8b-896f-4d245446457f"
}