{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T16:21:07Z","timestamp":1778602867580,"version":"3.51.4"},"reference-count":73,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T00:00:00Z","timestamp":1752796800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Medical Informatics"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1016\/j.ijmedinf.2025.106051","type":"journal-article","created":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T16:57:13Z","timestamp":1752857833000},"page":"106051","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":30,"special_numbering":"C","title":["Bridging the digital divide: artificial intelligence as a catalyst for health equity in primary care settings"],"prefix":"10.1016","volume":"204","author":[{"given":"Ayokunle","family":"Osonuga","sequence":"first","affiliation":[]},{"given":"Adewoyin A.","family":"Osonuga","sequence":"additional","affiliation":[]},{"given":"Sandra Chinaza","family":"Fidelis","sequence":"additional","affiliation":[]},{"given":"Gloria C.","family":"Osonuga","sequence":"additional","affiliation":[]},{"given":"Jack","family":"Juckes","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0188-9836","authenticated-orcid":false,"given":"David B.","family":"Olawade","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"Suppl 1","key":"10.1016\/j.ijmedinf.2025.106051_b0005","article-title":"Artificial intelligence and health inequities in primary care: a systematic scoping review and framework","volume":"10","author":"d'Elia","year":"2022","journal-title":"Fam Med Community Health."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0010","doi-asserted-by":"crossref","DOI":"10.3389\/fdgth.2024.1330160","article-title":"Accelerating health disparities research with artificial intelligence","volume":"6","author":"Green","year":"2024","journal-title":"Front Digit Health."},{"issue":"16","key":"10.1016\/j.ijmedinf.2025.106051_b0015","doi-asserted-by":"crossref","first-page":"5856","DOI":"10.3390\/ijerph17165856","article-title":"The social determinants of health: time to rethink?","volume":"17","author":"Frank","year":"2020","journal-title":"Int. J. Environ. Res. Public Health"},{"issue":"12","key":"10.1016\/j.ijmedinf.2025.106051_b0020","doi-asserted-by":"crossref","first-page":"866","DOI":"10.7326\/M18-1990","article-title":"Ensuring fairness in machine learning to advance health equity","volume":"169","author":"Rajkomar","year":"2018","journal-title":"Ann. Intern. Med."},{"issue":"4","key":"10.1016\/j.ijmedinf.2025.106051_b0025","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1056\/NEJMra2204673","article-title":"Artificial intelligence in U.S. health care delivery","volume":"389","author":"Sahni","year":"2023","journal-title":"N. Engl. J. Med."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0030","doi-asserted-by":"crossref","first-page":"E64","DOI":"10.5888\/pcd21.240245","article-title":"Health equity and ethical considerations in using artificial intelligence in public health and medicine","volume":"21","author":"Dankwa-Mullan","year":"2024","journal-title":"Prev. Chronic Dis."},{"issue":"10","key":"10.1016\/j.ijmedinf.2025.106051_b0035","article-title":"A systematic review of the barriers to the implementation of artificial intelligence in healthcare","volume":"15","author":"Ahmed","year":"2023","journal-title":"Cureus"},{"issue":"3","key":"10.1016\/j.ijmedinf.2025.106051_b0040","first-page":"28","article-title":"Understanding the challenges of language barriers in healthcare","volume":"3","author":"Organi","year":"2024","journal-title":"Interdiscip Stud Soc Law Polit."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.jth.2024.101819","article-title":"Impact of distance and\/or travel time on healthcare service access in rural and remote areas: a scoping review","volume":"37","author":"Mseke","year":"2024","journal-title":"J. Transp. Health"},{"issue":"1","key":"10.1016\/j.ijmedinf.2025.106051_b0050","doi-asserted-by":"crossref","first-page":"40","DOI":"10.7861\/fhj.2020-0233","article-title":"Implicit bias in healthcare: clinical practice, research, and decision making","volume":"8","author":"Gopal","year":"2021","journal-title":"Future Healthc J."},{"issue":"6","key":"10.1016\/j.ijmedinf.2025.106051_b0055","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0234926","article-title":"Communication and shared decision-making with patients with limited health literacy: helpful strategies, barriers, and suggestions for improvement reported by hospital-based palliative care providers","volume":"15","author":"Roodbeen","year":"2020","journal-title":"PLoS One"},{"key":"10.1016\/j.ijmedinf.2025.106051_b0060","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1002\/hpja.387","article-title":"Health literacy, digital health literacy, and the implementation of digital health technologies in cancer care: the need for a strategic approach","volume":"32","author":"Kemp","year":"2021","journal-title":"Health Promot. J. Austr."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0065","doi-asserted-by":"crossref","DOI":"10.2196\/55766","article-title":"Health care professionals' experience of using AI: Systematic review with narrative synthesis","volume":"26","author":"Ayorinde","year":"2024","journal-title":"J. Med. Internet Res."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0070","first-page":"1","article-title":"Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: a mixed-methods study","volume":"5","author":"Nadarzynski","year":"2019","journal-title":"Digit Health."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0075","doi-asserted-by":"crossref","DOI":"10.2196\/46159","article-title":"Social determinants of health documentation in structured and unstructured clinical data of patients with diabetes: comparative analysis","volume":"11","author":"Mehta","year":"2023","journal-title":"JMIR Med. Inform."},{"issue":"3","key":"10.1016\/j.ijmedinf.2025.106051_b0080","doi-asserted-by":"crossref","first-page":"324","DOI":"10.3390\/healthcare13030324","article-title":"Investigation into application of AI and telemedicine in rural communities: a systematic literature review","volume":"13","author":"Singh","year":"2025","journal-title":"Healthcare"},{"issue":"3","key":"10.1016\/j.ijmedinf.2025.106051_b0085","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1007\/s00779-021-01625-1","article-title":"AI-powered cloud for COVID-19 and other infectious disease diagnosis","volume":"27","author":"Al-Turjman","year":"2023","journal-title":"Pers Ubiquitous Comput."},{"issue":"3","key":"10.1016\/j.ijmedinf.2025.106051_b0090","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1097\/NCN.0b013e3181d785d5","article-title":"Use of three computer training methods in elderly underserved rural patients enrolled in a diabetes telemedicine program","volume":"28","author":"Robinson","year":"2010","journal-title":"Comput. Inform. Nurs."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0095","doi-asserted-by":"crossref","first-page":"e2476","DOI":"10.7717\/peerj-cs.2476","article-title":"Diagnostic test accuracy of AI-assisted mammography for breast imaging: a narrative review","volume":"11","author":"Dave","year":"2025","journal-title":"PeerJ Comput. Sci."},{"issue":"12","key":"10.1016\/j.ijmedinf.2025.106051_b0100","doi-asserted-by":"crossref","first-page":"2024","DOI":"10.1093\/jamia\/ocaa085","article-title":"Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning","volume":"27","author":"McCradden","year":"2020","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"6464","key":"10.1016\/j.ijmedinf.2025.106051_b0105","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1126\/science.aax2342","article-title":"Dissecting racial bias in an algorithm used to manage the health of populations","volume":"366","author":"Obermeyer","year":"2019","journal-title":"Science"},{"issue":"5","key":"10.1016\/j.ijmedinf.2025.106051_b0110","doi-asserted-by":"crossref","first-page":"1062","DOI":"10.1177\/17456916221134490","article-title":"A call to action on assessing and mitigating bias in artificial intelligence applications for mental health","volume":"18","author":"Timmons","year":"2023","journal-title":"Perspect. Psychol. Sci."},{"issue":"2","key":"10.1016\/j.ijmedinf.2025.106051_b0115","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1007\/s10916-021-01790-z","article-title":"Trustworthy augmented intelligence in health care","volume":"46","author":"Crigger","year":"2022","journal-title":"J. Med. Syst."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0120","unstructured":"Boldyga R. Rural healthcare challenges: How AI & telemedicine can improve access. HIT Consult. 2025 May 27. https:\/\/hitconsultant.net\/2025\/05\/27\/rural-healthcare-challenges-how-ai-telemedicine-can-improve-access\/."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0125","article-title":"Wearable Health Devices have Low Uptake among individuals with Heart Disease","author":"Klein","year":"2022","journal-title":"Am. J. Manag. Care"},{"key":"10.1016\/j.ijmedinf.2025.106051_b0130","doi-asserted-by":"crossref","DOI":"10.3389\/fdgth.2023.1264780","article-title":"Improving health literacy using the power of digital communications to achieve better health outcomes for patients and practitioners","volume":"5","author":"Fitzpatrick","year":"2023","journal-title":"Front Digit Health."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0135","unstructured":"M. Gilman, R. GreenThe surveillance gap: the harms of extreme privacy and data marginalizationNYU Rev L Soc Change.422018253."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0140","doi-asserted-by":"crossref","first-page":"102895","DOI":"10.1016\/j.jflm.2025.102895","article-title":"Artificial Intelligence in Forensic Mental Health: A Review of Applications and Implications","volume":"24","author":"Olawade","year":"2025","journal-title":"Journal of Forensic and Legal Medicine"},{"issue":"4","key":"10.1016\/j.ijmedinf.2025.106051_b0145","doi-asserted-by":"crossref","DOI":"10.2196\/29535","article-title":"Digital health\u2013enabled community-centered care: scalable model to empower future community health workers using human-in-the-loop artificial intelligence","volume":"6","author":"Rodrigues","year":"2022","journal-title":"JMIR Form Res."},{"issue":"4","key":"10.1016\/j.ijmedinf.2025.106051_b0150","first-page":"582","article-title":"Treating health disparities with artificial intelligence","volume":"27","author":"Chen","year":"2021","journal-title":"Nat. Med."},{"issue":"9","key":"10.1016\/j.ijmedinf.2025.106051_b0155","first-page":"e449","article-title":"Applications of digital technology in COVID-19 pandemic planning and response","volume":"2","author":"Whitelaw","year":"2020","journal-title":"Lancet Digit Health."},{"issue":"8","key":"10.1016\/j.ijmedinf.2025.106051_b0160","doi-asserted-by":"crossref","first-page":"1028","DOI":"10.1093\/jamia\/ocy052","article-title":"Good intentions are not enough: how informatics interventions can worsen inequality","volume":"25","author":"Veinot","year":"2018","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0165","series-title":"Race after technology: Abolitionist tools for the new Jim Code","author":"Benjamin","year":"2019"},{"issue":"7","key":"10.1016\/j.ijmedinf.2025.106051_b0170","first-page":"669","article-title":"The potential for artificial intelligence in healthcare","volume":"321","author":"Davenport","year":"2019","journal-title":"JAMA"},{"key":"10.1016\/j.ijmedinf.2025.106051_b0175","doi-asserted-by":"crossref","unstructured":"Leslie D. Understanding artificial intelligence ethics and safety: A guide for the responsible design and implementation of AI systems in the public sector. London (UK): The Alan Turing Institute; 2020. https:\/\/doi.org\/10.5281\/zenodo.3240529.","DOI":"10.2139\/ssrn.3403301"},{"issue":"3","key":"10.1016\/j.ijmedinf.2025.106051_b0180","article-title":"A governance model for the application of AI in health care","volume":"27","author":"Reddy","year":"2020","journal-title":"BMJ Health Care Inform."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0185","series-title":"Ethics and governance of artificial intelligence for health","author":"World Health Organization","year":"2021"},{"issue":"1","key":"10.1016\/j.ijmedinf.2025.106051_b0190","first-page":"12","article-title":"Bias in AI-based medical tools: Gaps in demographic reporting","volume":"5","author":"Obermeyer","year":"2023","journal-title":"Nat. Mach. Intell."},{"issue":"1","key":"10.1016\/j.ijmedinf.2025.106051_b0195","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1007\/s11831-024-10134-2","article-title":"A comprehensive review of bias in deep learning models: Methods, impacts, and future directions","volume":"32","author":"Shah","year":"2025","journal-title":"Arch. Comput. Methods Eng."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0200","series-title":"Algorithmic accountability in health care: a regulatory framework","author":"Leslie","year":"2021"},{"issue":"4","key":"10.1016\/j.ijmedinf.2025.106051_b0205","first-page":"211","article-title":"Co-designing health technologies: Involving communities to build equity","volume":"12","author":"Black","year":"2020","journal-title":"J Particip Med."},{"issue":"2","key":"10.1016\/j.ijmedinf.2025.106051_b0210","first-page":"215","article-title":"Transparency and interpretability of FDA-cleared AI medical devices: a review of public disclosures","volume":"30","author":"Nguyen","year":"2023","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0215","unstructured":"IBM. Global AI Adoption Index 2021. IBM Research; 2021."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0220","series-title":"Artificial intelligence in clinical settings: evidence, equity, and ethics","author":"Zulman","year":"2023"},{"issue":"12","key":"10.1016\/j.ijmedinf.2025.106051_b0225","doi-asserted-by":"crossref","first-page":"2176","DOI":"10.1038\/s41591-021-01595-0","article-title":"Underdiagnosis bias of AI algorithms in chest X-ray classification","volume":"27","author":"Seyyed-Kalantari","year":"2021","journal-title":"Nat. Med."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0230","unstructured":"American Medical Association. Digital health research: Physicians' motivations and requirements for adopting digital health tools. Chicago: AMA; 2022. assn.org\/system\/files\/digital-health-research-2022.pdf."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0235","series-title":"Community-informed AI governance in healthcare","author":"Richards","year":"2021"},{"issue":"2","key":"10.1016\/j.ijmedinf.2025.106051_b0240","doi-asserted-by":"crossref","DOI":"10.1148\/radiol.232750","article-title":"Six steps to improving Health Equity using Quality Improvement and Patient Safety Tools","volume":"314","author":"Narayan","year":"2025","journal-title":"Radiology"},{"key":"10.1016\/j.ijmedinf.2025.106051_b0245","series-title":"Participatory data stewardship: a framework for involving people in the use of data","author":"Ada Lovelace Institute","year":"2022"},{"key":"10.1016\/j.ijmedinf.2025.106051_b0250","series-title":"Principled artificial intelligence: Mapping consensus in ethical and rights-based approaches to principles for AI","author":"Fjeld","year":"2020"},{"key":"10.1016\/j.ijmedinf.2025.106051_b0255","series-title":"Artificial Intelligence in Health Care: the Hope, the Hype, the Promise, the Peril","author":"National Academy of Medicine","year":"2022"},{"issue":"6","key":"10.1016\/j.ijmedinf.2025.106051_b0260","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1001\/jama.2019.21579","article-title":"Artificial intelligence in health care: a report from the National Academy of Medicine","volume":"323","author":"Matheny","year":"2022","journal-title":"JAMA"},{"issue":"1","key":"10.1016\/j.ijmedinf.2025.106051_b0265","first-page":"28694","article-title":"A new governance space for health","volume":"9","author":"Kickbusch","year":"2016","journal-title":"Glob. Health Action"},{"issue":"7","key":"10.1016\/j.ijmedinf.2025.106051_b0270","doi-asserted-by":"crossref","first-page":"699","DOI":"10.1001\/jama.2013.108769","article-title":"Improved blood pressure control associated with a large-scale hypertension program","volume":"310","author":"Jaffe","year":"2013","journal-title":"JAMA"},{"issue":"5","key":"10.1016\/j.ijmedinf.2025.106051_b0275","first-page":"544","article-title":"Systemic implementation strategies to improve hypertension: the Kaiser Permanente Southern California experience","volume":"30","author":"Sim","year":"2014","journal-title":"Can. J. Cardiol."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0280","doi-asserted-by":"crossref","unstructured":"Fontil V, Gupta R, Moise N, Chen E, Guzman D, McCulloch CE, Bibbins-Domingo K. Adapting and evaluating a health system intervention from Kaiser Permanente to improve hypertension management and control in a large network of safety-net clinics. Circulation: Cardiovascular Quality and Outcomes. 2018 Jul;11(7):e004386.","DOI":"10.1161\/CIRCOUTCOMES.117.004386"},{"issue":"8","key":"10.1016\/j.ijmedinf.2025.106051_b0285","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.1001\/jamainternmed.2021.2626","article-title":"External validation of a widely implemented proprietary sepsis prediction model in hospitalized patients","volume":"181","author":"Wong","year":"2021","journal-title":"JAMA Intern. Med."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0290","doi-asserted-by":"crossref","unstructured":"Ostermayer DG, Braunheim B, Mehta AM, Ward J, Andrabi S, Sirajuddin AM. External validation of the Epic sepsis predictive model in 2 county emergency departments. JAMIA open. 2024 Dec;7(4):ooae133.","DOI":"10.1093\/jamiaopen\/ooae133"},{"issue":"10","key":"10.1016\/j.ijmedinf.2025.106051_b0295","doi-asserted-by":"crossref","first-page":"3188","DOI":"10.1007\/s11606-021-06846-x","article-title":"Health care equity in the use of advanced analytics and artificial intelligence technologies in primary care","volume":"36","author":"Clark","year":"2021","journal-title":"J. Gen. Intern. Med."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0300","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.breast.2019.12.006","article-title":"Improving breast cancer care coordination and symptom management by using AI driven predictive toolkits","volume":"50","author":"Moser","year":"2020","journal-title":"Breast"},{"issue":"13","key":"10.1016\/j.ijmedinf.2025.106051_b0305","article-title":"Improving AI-based clinical decision support systems and their integration into care from the perspective of experts: interview study among different stakeholders","volume":"7","author":"Giebel","year":"2025","journal-title":"JMIR Med. Inform."},{"issue":"2","key":"10.1016\/j.ijmedinf.2025.106051_b0310","doi-asserted-by":"crossref","DOI":"10.1161\/CIRCIMAGING.123.015495","article-title":"Machine learning and bias in medical imaging: opportunities and challenges","volume":"17","author":"Vrudhula","year":"2024","journal-title":"Circ. Cardiovasc. Imaging"},{"key":"10.1016\/j.ijmedinf.2025.106051_b0315","series-title":"Artificial Intelligence in Biomedical and Health Research: Cross-Country Data Representation","author":"National Institutes of Health","year":"2021"},{"key":"10.1016\/j.ijmedinf.2025.106051_b0320","series-title":"CHI 2020 Conference on Human Factors in Computing Systems","first-page":"1","article-title":"A human-centered evaluation of a deep learning system deployed in clinics for the detection of diabetic retinopathy","author":"Beede","year":"2020"},{"issue":"6","key":"10.1016\/j.ijmedinf.2025.106051_b0325","first-page":"1","article-title":"Leveraging health data analytics to drive inclusive Medicaid expansion and immigrant healthcare policy reform","volume":"14","author":"Agyemang","year":"2025","journal-title":"Int J Comput Appl Technol Res."},{"issue":"6","key":"10.1016\/j.ijmedinf.2025.106051_b0330","first-page":"376","article-title":"The Role of Artificial Intelligence in Immigration Law Enforcement: Balancing Efficiency, Transparency, and Ethical Accountability","volume":"1","author":"Hamdi","year":"2024","journal-title":"Journal of Multidisciplinary Sustainability Asean."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0335","series-title":"Intersectionality in AI: evaluating health technologies through multidimensional equity","author":"AI Now Institute","year":"2023"},{"key":"10.1016\/j.ijmedinf.2025.106051_b0340","unstructured":"Magnan S. Social determinants of health 101 for health care: Five plus five. NAM Perspect. 2017. https:\/\/mimultipayerinitiatives.org\/wp-content\/uploads\/2024\/07\/sdoh-discussion-paper-101-for-health-care.pdf."},{"issue":"3","key":"10.1016\/j.ijmedinf.2025.106051_b0345","doi-asserted-by":"crossref","DOI":"10.2196\/13802","article-title":"Assessing the availability of data on social and behavioral determinants in structured and unstructured electronic health records: a retrospective analysis of a multilevel health care system","volume":"7","author":"Hatef","year":"2019","journal-title":"JMIR Med. Inform."},{"issue":"3","key":"10.1016\/j.ijmedinf.2025.106051_b0350","doi-asserted-by":"crossref","first-page":"244","DOI":"10.20517\/ir.2022.17","article-title":"A review of causality-based fairness machine learning","volume":"2","author":"Su","year":"2022","journal-title":"Intelligence & Robotics."},{"issue":"12","key":"10.1016\/j.ijmedinf.2025.106051_b0355","doi-asserted-by":"crossref","first-page":"2716","DOI":"10.1093\/jamia\/ocab170","article-title":"Extracting social determinants of health from electronic health records using natural language processing: a systematic review","volume":"28","author":"Patra","year":"2021","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"10.1016\/j.ijmedinf.2025.106051_b0360","doi-asserted-by":"crossref","unstructured":"Ogwu MC, Izah SC. Artificial Intelligence and Machine Learning in Tropical Disease Management. InTechnological Innovations for Managing Tropical Diseases 2025 Feb 20 (pp. 155-182). Cham: Springer Nature Switzerland.","DOI":"10.1007\/978-3-031-82622-1_7"},{"issue":"149","key":"10.1016\/j.ijmedinf.2025.106051_b0365","article-title":"The EU artificial intelligence act (2024): implications for healthcare","volume":"1","author":"Van Kolfschooten","year":"2024","journal-title":"Health Policy"}],"container-title":["International Journal of Medical Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1386505625002680?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1386505625002680?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,5]],"date-time":"2025-09-05T06:14:58Z","timestamp":1757052898000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1386505625002680"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12]]},"references-count":73,"alternative-id":["S1386505625002680"],"URL":"https:\/\/doi.org\/10.1016\/j.ijmedinf.2025.106051","relation":{},"ISSN":["1386-5056"],"issn-type":[{"value":"1386-5056","type":"print"}],"subject":[],"published":{"date-parts":[[2025,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Bridging the digital divide: artificial intelligence as a catalyst for health equity in primary care settings","name":"articletitle","label":"Article Title"},{"value":"International Journal of Medical Informatics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ijmedinf.2025.106051","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Authors. Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"106051"}}