{ "abstract": "Artificial intelligence (AI) is rapidly transforming healthcare. Yet people with disabilities (PWD), representing 16% of the global population, remain disproportionately excluded from these advances. This exclusion is driven by algorithmic bias, non-representative datasets, and limited involvement of PWD in the design, development, and evaluation of AI applications. This scoping review examines the extent to which AI research in health contributes to the development of inclusive technologies for PWD, focusing on equity considerations. It identifies current trends, methodological gaps, and opportunities for socially responsive innovation. We conducted a systematic search across MEDLINE, Embase, Web of Science, and CINAHL for the 2015–2025 period, following Arksey and O’Malley’s five-stage scoping review methodology and the PRISMA-ScR guidelines. Data were extracted and synthesized thematically using the Population-Concept-Context approach. Of 4,233 references retrieved, 93 studies were included. Most studies originated from high-income countries, particularly in North America (45.2%) and Europe (26.9%). AI applications addressed motor, sensory, cognitive, communication-related, and psychosocial disabilities, with emphasis on prediction/diagnosis, assistive technologies, and personalized care. While about 60% of studies referenced equity, only 12 (12.9%) implemented concrete measures (e.g., adapting tools for vulnerable groups or ensuring sample diversity), and only six (6.5%) actively involved PWD through co-design or user validation. AI holds significant potential to enhance autonomy, access, and quality of life for PWD. Realizing this promise will require moving beyond technical optimization to embrace inclusive design, participatory methods, and equity-driven frameworks aligned with responsible AI development and use. Author summary: People with disabilities (PWD) are frequently underrepresented in the design, development, implementation, and evaluation of artificial intelligence (AI) systems, which can limit the accessibility, usability, and equity of these technologies, and result failing to address their diverse needs and lived experiences. It is therefore essential to evaluate the extent to which PWD are meaningfully involved across all stages of AI development and research. In this scoping review, we examined their roles from multiple perspectives. Our review explored how healthcare AI research contributes to the development of inclusive and accessible technologies for PWD. We identified studies addressing a wide range of disabilities and AI applications, including predictive models, assistive technologies, early screening tools, and decision-support systems. Overall, our findings highlight the growing recognition of inclusive AI development while demonstrating that meaningful participation, accessibility, transparency, and context-sensitive implementation remain inconsistently addressed. Based on these findings, we identify key gaps in the current literature and provide recommendations to guide the development of more equitable, accessible, and person-centered AI systems for people with disabilities.", "abstract_shown": true, "affiliations": [ "École d’optométrie, Université de Montréal, Montréal, Québec, Canada", "Centre de Recherche Interdisciplinaire en Réadaptation du Montréal métropolitain, Montréal, Québec, Canada", "Centre de recherche en santé publique, Montréal, Québec, Canada", "École de santé publique, Université de Montréal, Montréal, Québec, Canada" ], "article_type": "Research Article", "arxiv": null, "author_total": 6, "authors": [ { "affs": [ 0 ], "name": "Soutongnoma Safiata Kaboré" }, { "affs": [ 1 ], "name": "Azadeh Bayani" }, { "affs": [ 2 ], "name": "Léandre Parfait Epoh Ewane" }, { "affs": [ 3 ], "name": "Davllyn Santos Oliveira dos Anjos" }, { "name": "Jean Noel Nikiéma" }, { "name": "Muriel Mac-Seing" } ], "bibtex": "https://research.draconitic.com/paper/5zwwqqc88d88f.bib", "cited_by": 0, "doi": "10.1371/journal.pdig.0001749", "fulltext_url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001749", "id": "5zwwqqc88d88f", "issns": [ "2767-3170" ], "landing_url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001749", "language": "eng", "licence": "CC-BY", "licence_label": "CC BY", "licence_source": "article", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "metadata_licence": null, "native_subjects": [ [ "openalex", "3311|Ethics and Social Impacts of AI" ], [ "plos", "/Biology and life sciences/Bioengineering/Biotechnology/Medical devices and equipment/Assistive technologies" ], [ "plos", "/Computer and information sciences/Artificial intelligence" ], [ "plos", "/Earth sciences/Geography/Economic geography/Low and middle income countries" ], [ "plos", "/Engineering and technology/Bioengineering/Biotechnology/Medical devices and equipment/Assistive technologies" ], [ "plos", "/Medicine and health sciences/Epidemiology/Medical risk factors" ], [ "plos", "/Medicine and health sciences/Medical conditions/Disabilities" ], [ "plos", "/Medicine and health sciences/Medical conditions/Neurodegenerative diseases/Alzheimer's disease" ], [ "plos", "/Medicine and health sciences/Medical devices and equipment/Assistive technologies" ], [ "plos", "/Medicine and health sciences/Mental health and psychiatry/Dementia/Alzheimer's disease" ], [ "plos", "/Medicine and health sciences/Neurology/Dementia/Alzheimer's disease" ], [ "plos", "/Medicine and health sciences/Neurology/Neurodegenerative diseases/Alzheimer's disease" ], [ "plos", "/Medicine and health sciences/Ophthalmology/Visual impairments" ], [ "plos", "/Physical sciences/Mathematics/Statistics/Statistical methods/Forecasting" ], [ "plos", "/Research and analysis methods/Mathematical and statistical techniques/Statistical methods/Forecasting" ], [ "plos", "/Social sciences/Economics/Economic geography/Low and middle income countries" ] ], "openalex": "W7222238123", "pdf_url": "https://journals.plos.org/digitalhealth/article/file?id=10.1371/journal.pdig.0001749&type=printable", "pmcid": "PMC13671530", "pmid": null, "published": "2026-10-01", "publisher": "Public Library of Science", "ris": "https://research.draconitic.com/paper/5zwwqqc88d88f.ris", "sources": [ { "first_seen": "2026-10-30T12:17:23Z", "native_id": "10.1371/journal.pdig.0001749", "source": "plos", "url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001749" }, { "first_seen": "2026-10-30T12:18:29Z", "native_id": "PMC:PMC13671530", "source": "europepmc", "url": "https://europepmc.org/article/PMC/PMC13671530" } ], "subjects": [ { "field": "biology", "origin": "plos:biotechnology", "subfield": "systems-synthetic" }, { "field": "mathematics", "origin": "plos:statistical methods", "subfield": "statistics" }, { "field": "medicine", "origin": "plos:neurology", "subfield": "neurology" } ], "title": "Contribution of artificial intelligence research to the development of inclusive applications for people with disabilities: A scoping review (2015–2025)", "title_text": "Contribution of artificial intelligence research to the development of inclusive applications for people with disabilities: A scoping review (2015–2025)", "type": "peer-reviewed", "updated_at": "2026-10-30T12:18:29Z", "url": "https://research.draconitic.com/paper/5zwwqqc88d88f", "venue": "PLOS Digital Health", "versions": [] }