{
  "abstract": "Key Points: Current ILD guidelines centre diagnosis on clinical context, exposure and autoimmune assessment, high‐resolution CT, pulmonary function testing, and multidisciplinary discussion, while explicit endorsement of artificial intelligence remains limited.\n\nSome artificial intelligence tools have already entered ILD‐related clinical workflows by flagging interstitial abnormalities on routine CT, supporting non‐invasive assessment of suspected fibrotic ILD, and quantifying fibrotic burden and interval progression on serial imaging.\n\nResearch‐stage AI models are beginning to address unresolved gaps in clinical guidelines by reducing diagnostic uncertainty in borderline cases, enabling subgroup‐specific risk stratification in connective tissue disease‐associated ILD, and forecasting progression or follow‐up needs from longitudinal multimodal data.\n\nThe remaining need is to develop a validated personalised multimodal decision‐support system that can integrate imaging, clinical, serological, pathological, and longitudinal data to guide biopsy, surveillance, and management decisions for uncertain ILD cases.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine The University of Hong Kong Hong Kong SAR China",
    "The University of Hong Kong–Shenzhen Hospital China",
    "Centre for Safe Medication Practice and Research, Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine The University of Hong Kong Hong Kong SAR China"
  ],
  "article_type": "article commentary",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Deliang Yang",
      "orcid": "0000-0002-8250-8072"
    },
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Xue Li",
      "orcid": "0000-0003-4836-7808"
    },
    {
      "affs": [
        0
      ],
      "name": "David Chi Leung Lam",
      "orcid": "0000-0002-0004-2660"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4v8dmm0h4yxmq.bib",
  "cited_by": 0,
  "doi": "10.1002/resp.70298",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13728518/",
  "id": "4v8dmm0h4yxmq",
  "issns": [
    "1323-7799",
    "1440-1843"
  ],
  "landing_url": "https://doi.org/10.1002/resp.70298",
  "language": "en",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Commentary"
    ],
    [
      "openalex",
      "2740|Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis"
    ]
  ],
  "openalex": "W7202244829",
  "pdf_url": "https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/resp.70298",
  "pmcid": "PMC13728518",
  "pmid": "42581805",
  "published": "2026-08-12",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/4v8dmm0h4yxmq.ris",
  "sources": [
    {
      "first_seen": "2026-11-07T12:21:29Z",
      "native_id": "PMC13728518",
      "source": "pmc",
      "url": "https://doi.org/10.1002/resp.70298"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2740|Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis",
      "subfield": "general"
    }
  ],
  "title": "From Pattern Recognition to Decision Guidance: Artificial Intelligence in Interstitial Lung Disease Diagnosis and Surveillance",
  "title_text": "From Pattern Recognition to Decision Guidance: Artificial Intelligence in Interstitial Lung Disease Diagnosis and Surveillance",
  "type": "peer-reviewed",
  "updated_at": "2026-11-07T12:21:29Z",
  "url": "https://research.draconitic.com/paper/4v8dmm0h4yxmq",
  "venue": "Respirology (Carlton, Vic.)",
  "versions": []
}