Artificial intelligence in diabetes care: from predictive analytics to generative AI and implementation challenges
Rattachement africain : cn. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Generative artificial intelligence (GenAI) is transforming public health and medicine as well, in the form of disease surveillance, resource allocation and clinical decision making. Interventions to improve efficiency - multimodal predictive algorithms, federated learning platforms - reveal the internal contradictions of the system between algorithmic efficiency and fairness: speed of technical innovation and regulatory deficit, data flows without borders vs. ethical values of places. We present a three-dimensional governance structure for the topic covering the technical, institutional and ethical domains. From a technology point of view, explainability solutions and culturally-aware design align transparency with cultural sensibility. From an institution point of view, privacy-protecting data platforms and risk-based regulation align innovation with accountability. From an ethical point of view, incorporating local values and disbursing AI dividends sustain equitable health outcomes. There are still challenges that demand the utmost priority, including the algorithmic prejudice, the data imperialism and the opacity in medical AI decision making. Future priorities include the development of broader measurement tools that integrate clinical impact, equity, and societal impact; the development of transnational governance institutions to mitigate concerns relating to data sovereignty; and the development of forms of participatory design between designers, practitioners, and populations. A balance between technical creativity, visionary policy-making, and caring leadership to advocate for human-centered healthcare will provide us with trusted AI ecosystems. Technical excellence alone cannot guarantee success unless fairness and accessibility, social responsiveness, and justice for future global health is guaranteed.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Artificial intelligence in diabetes care: from predictive analytics to generative AI and implementation challenges
- Date Crossref
- 19/11/2025
- Éditeur
- Frontiers Media SA
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Beijing Obstetrics and Gynecology Hospital pays non établi dans la noticeÉtablissement de santé
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Handan College pays non établi dans la noticeUniversité ou école supérieure
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Nanchang University Department of Educational Management pays non établi dans la noticeUniversité ou école supérieure
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Education Department of Jiangxi Province pays non établi dans la noticeOrganisme public
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Beijing Proteome Research Center pays non établi dans la noticeStructure de recherche
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Capital Medical University Department of Gynecological Oncology pays non établi dans la noticeUniversité ou école supérieure
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Handan Fukang Hospital Department of Gynecology and Obstetrics pays non établi dans la noticeÉtablissement de santé
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State Key Laboratory of Medical Proteomics pays non établi dans la noticeStructure de recherche
Beijing Obstetrics and Gynecology Hospital, Handan College et Department of Educational Management — Nanchang University, avec 5 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.