{
  "abstract": "The use of artificial intelligence (AI) is growing quickly in high-tech, people-dependent sectors, including healthcare. There is potential application in diagnostic cellular (anatomic) pathology as shown by the article by Jaeckle et al.1 In this paper, the authors describe a novel interpretable AI tool which analyses scanned whole slide histopathological images to diagnose coeliac disease. The tool can provide pathologists with quantitative estimates of relevant data—crypt to villus ratio, proportion of intraepithelial lymphocytes—to enhance diagnostic accuracy. Although not a rare diagnosis, coeliac disease is challenging because the criteria in question tend to be inconsistently determined by eye.",
  "authors": [
    {
      "affiliations": [
        "Pathology, NHS Grampian, Aberdeen, Scotland, UK",
        "Applied Medicine, University of Aberdeen, Aberdeen, Scotland, UK"
      ],
      "name": "Peter Johnston"
    }
  ],
  "title": "Socialising artificial intelligence in diagnostic cellular pathology",
  "uid": "432207b1-ad78-5f1f-933c-e32a19317f0f"
}