{
  "abstract": "Despite the promising potential of Artificial Intelligence (AI) models to enhance health equities for persons with disabilities, poorly designed applications risk exacerbating inequities. To address this, we conducted a narrative review using disability justice frameworks as an analytical lens to evaluate how AI applications operationalize disability and health equity across various domains. AI models demonstrate potential in early intervention, personalized care, equitable resource allocation, assistive technologies, and health surveillance. However, most AI models rely primarily on biomedical and functional data, often trained on biased datasets that neglect social and structural determinants of disability. As a result, these applications insufficiently capture broader dimensions of wellbeing, including capabilities, recognition, and structural justice, limiting their effectiveness in addressing health inequities. To advance health equity for persons with disabilities, AI applications must incorporate disability-inclusive datasets, participatory co-design with persons with disabilities, auditing for fairness, and real-world validation. Integrating clinical, social, and structural dimensions in a justice-oriented framework can help AI models move beyond narrow biomedical models toward more inclusive, context-sensitive, and equitable health systems.",
  "abstract_shown": true,
  "affiliations": [
    "Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland",
    "Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland",
    "HES-SO University of Applied Arts Sciences and Arts of Western Switzerland, Geneva, Switzerland"
  ],
  "article_type": "Review",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Jyoti Dalal"
    },
    {
      "affs": [
        1
      ],
      "name": "Douglas Teodoro"
    },
    {
      "affs": [
        2
      ],
      "name": "Minerva Rivas Velarde"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ab9dzwypeap6r.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pdig.0001663",
  "fulltext_url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001663",
  "id": "ab9dzwypeap6r",
  "issns": [
    "2767-3170"
  ],
  "landing_url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001663",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2718|Artificial Intelligence in Healthcare and Education"
    ],
    [
      "plos",
      "/Biology and life sciences/Anatomy/Ocular system/Ocular anatomy/Eye lens"
    ],
    [
      "plos",
      "/Biology and life sciences/Bioengineering/Biotechnology/Medical devices and equipment/Assistive technologies"
    ],
    [
      "plos",
      "/Computer and information sciences/Artificial intelligence"
    ],
    [
      "plos",
      "/Computer and information sciences/Artificial intelligence/Machine learning"
    ],
    [
      "plos",
      "/Computer and information sciences/Information technology/Natural language processing"
    ],
    [
      "plos",
      "/Engineering and technology/Bioengineering/Biotechnology/Medical devices and equipment/Assistive technologies"
    ],
    [
      "plos",
      "/Medicine and health sciences/Anatomy/Ocular system/Ocular anatomy/Eye lens"
    ],
    [
      "plos",
      "/Medicine and health sciences/Medical conditions/Disabilities"
    ],
    [
      "plos",
      "/Medicine and health sciences/Medical devices and equipment/Assistive technologies"
    ],
    [
      "plos",
      "/Medicine and health sciences/Public and occupational health/Behavioral and social aspects of health"
    ],
    [
      "plos",
      "/Medicine and health sciences/Public and occupational health/Global health"
    ]
  ],
  "openalex": "W7204901848",
  "pdf_url": "https://journals.plos.org/digitalhealth/article/file?id=10.1371/journal.pdig.0001663&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-01",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/ab9dzwypeap6r.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:02Z",
      "native_id": "10.1371/journal.pdig.0001663",
      "source": "plos",
      "url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001663"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "plos:biotechnology",
      "subfield": "systems-synthetic"
    },
    {
      "field": "medicine",
      "origin": "plos:public and occupational health",
      "subfield": "epidemiology-public-health"
    },
    {
      "field": "medicine",
      "origin": "plos:anatomy",
      "subfield": "physiology"
    }
  ],
  "title": "The promise and peril of AI for disability health equity: A justice-centered narrative review",
  "title_text": "The promise and peril of AI for disability health equity: A justice-centered narrative review",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:02Z",
  "url": "https://research.draconitic.com/paper/ab9dzwypeap6r",
  "venue": "PLOS Digital Health",
  "versions": []
}