[1] Foo D, Mahadeva J, Lopez F, et al. High-performing primary care: Reinvigorating general practice as a learning health system [J]. British Journal of General Practice, 2023, 73(726): 8-9.
[2] Pettigrew R I. Enter the physicianeers: How they will transform health care [J]. JAMA, 2025, 333(8): 667.
[3] Karregat E P M, Vooijs P, Wierda E, et al. Patient experiences with a smartwatch 1L-ECG versus traditional Holter monitoring for ambulatory cardiac rhythm monitoring: A qualitative study [J]. BMJ Open, 2025, 15(12): e101557.
[4] Hill N R, Groves L, Dickerson C, et al. Identification of undiagnosed atrial fibrillation using a machine learning risk-prediction algorithm and diagnostic testing (PULsE-AI) in primary care: A multi-centre randomized controlled trial in England [J]. European Heart Journal - Digital Health, 2022, 3(2): 195-204.
[5] Stefanovic M, Trifunovic-Zamaklar D, Mladenovic Z, et al. Utility of Mobile phone app-assisted screening for heart failure in primary care: Insights from the ECHOS3 registry [J]. International Journal of Cardiology, 2025, 439: 133651.
[6] Tao L Y, Liu J, Lu X Q, et al. Performance of the large language model in general medicine [J]. Global Transitions, 2026, 8(1): 101-109.
[7] Huang X Y, Sun M, Shen C X, et al. Visual-language reasoning large language models for primary care: Advancing clinical decision support through multimodal AI [J]. The Visual Computer, 2025, 41(13): 11327-11348.
[8] Yang X, Chen A K, PourNejatian N, et al. A large language model for electronic health records [J]. npj Digital Medicine, 2022, 5: 194.
[9] Kaye R, Arvanitis T N, Lim Choi Keung S N, et al. Implementing digitally enabled integrated healthcare [J]. Journal of Integrated Care, 2024, 32(5): 25-36.
[10] Larrañaga I, Mar J, Gorostiza A, et al. Evaluation of the epidemiological and economic impact of the ADLIFE intervention on medium- to long-term in patients with advanced chronic disease [J]. Frontiers in Public Health, 2025, 13: 1682492.
[11] Petrie S, Simard A, Innes E, et al. Bringing care close to home: Remote management of heart failure in partnership with indigenous communities in northern Ontario, Canada [J]. CJC Open, 2024, 6(12): 1423-1433.
[12] Silverstein W K, Lawrason S, Carabuena I, et al. A remote management-centric postdischarge pathway for patients admitted to GIM with heart failure [J]. The American Journal of Medicine, 2025, 138(5): 901-905.
[13] WHO. Integrating NCD diagnosis into remote primary care in the Maldives [EB/OL]. (2025-02-27) [2026-01-26]. https://www.who.int/news-room/feature-stories/detail/integrating-ncd-diagnosis-into-remote-primary-care-in-the-maldives.
[14] Bassi A, Arora V, Arfin S, et al. Preliminary effectiveness and feasibility of ASHA-led mobile health intervention for diabetes care in Indian primary health care settings [J]. Scientific Reports, 2025, 15: 36712.
[15] Gong E Y, Sun L X, Long Q, et al. The implementation of a primary care-based integrated mobile health intervention for stroke management in rural China: Mixed-methods process evaluation [J]. Frontiers in Public Health, 2021, 9: 774907.
[16] Garg V, Markan S, Malhotra C, et al. Revolutionizing healthcare access: Exploring the potential of telehealth kiosks [M]//Innovations in healthcare technologies in India. Singapore: Springer, 2025: 61-70.
[17] de Almeida Lamas C, Santana Alves P G, Nader de Araújo L, et al. Telehealth initiative to enhance primary care access in Brazil (UBS+Digital project): Multicenter prospective study [J]. Journal of Medical Internet Research, 2025, 27: e68434.
[18] Xie Y, Zhang H N, Li W Q, et al. Impact of Health All-in-One Machines on access to healthcare of rural areas in China: An interrupted time series analysis [J]. BMC Health Services Research, 2025, 25(1): 537.
[19] Kim D J, Lee Y S, Jeon E R, et al. Present and future of AI-IoT-based healthcare services for senior citizens in local communities: A review of a South Korean government digital healthcare initiatives [J]. Healthcare, 2024, 12(2): 281.
[20] Tene T, Bonilla García N, Coello-Fiallos D, et al. A systematic review of immersive educational technologies in medical physics and radiation physics [J]. Frontiers in Medicine, 2024, 11: 1384799.
[21] Constable M D, Zhang F X, Conner T, et al. Advancing healthcare practice and education via data sharing: Demonstrating the utility of open data by training an artificial intelligence model to assess cardiopulmonary resuscitation skills [J]. Advances in Health Sciences Education, 2025, 30(1): 15-35.
[22] Asiimwe R, Lam S, Leung S, et al. From biobank and data silos into a data commons: Convergence to support translational medicine [J]. Journal of Translational Medicine, 2021, 19(1): 493.
[23] Passman R. Mobile health technologies in the diagnosis and management of atrial fibrillation [J]. Current Opinion in Cardiology, 2022, 37(1): 1-9.
[24] Abd-Alrazaq A, Solaiman B, Mekki Y M, et al. Hype vs reality in the integration of artificial intelligence in clinical workflows [J]. JMIR Formative Research, 2025, 9: e70921.
[25] Obermeyer Z, Powers B, Vogeli C, et al. Dissecting racial bias in an algorithm used to manage the health of populations [J]. Science, 2019, 366(6464): 447-453.
[26] Kasoju N, Remya N S, Sasi R, et al. Digital health: Trends, opportunities and challenges in medical devices, pharma and bio-technology [J]. CSI Transactions on ICT, 2023, 11(1): 11-30.
[27] Pucchio A, Del Papa J, de Moraes F Y. Artificial intelligence in the medical profession: Ready or not, here AI comes [J]. Clinics, 2022, 77: 100010.
[28] Murad D A, Tsugawa Y, Elashoff D A, et al. Distinct components of alert fatigue in physicians’ responses to a noninterruptive clinical decision support alert [J]. Journal of the American Medical Informatics Association, 2022, 30(1): 64-72.
[29] Andrew A. Potential applications and implications of large language models in primary care [J]. Family Medicine and Community Health, 2024, 12(Suppl 1): e002602.
[30] Mathews S C, McShea M J, Hanley C L, et al. Digital health: A path to validation [J]. npj Digital Medicine, 2019, 2: 38.
[31] Ong J C L, Chang S Y, William W, et al. Ethical and regulatory challenges of large language models in medicine [J]. The Lancet Digital Health, 2024, 6(6): e428-e432.
[32] Shaw J A, Donia J. The sociotechnical ethics of digital health: A critique and extension of approaches from bioethics [J]. Frontiers in Digital Health, 2021, 3: 725088.
[33] Markus A F, Kors J A, Rijnbeek P R. The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategies [J]. Journal of Biomedical Informatics, 2021, 113: 103655.
[34] Shahin D, Sostorecz S, Shariff A, et al. Role of artificial intelligence (AI) in family medicine [M]// Artificial intelligence in medicine and surgery - An exploration of current trends, potential opportunities, and evolving threats, Volume 3. London: IntechOpen, 2026: 8.
[35] Wang Q W, Cui T T, Deng P W. Medicine-engineering interdisciplinary research based on bibliometric analysis: A case study on medicine-engineering institutional cooperation of Shanghai Jiao Tong University [J]. Journal of Shanghai Jiao Tong University (Science), 2023, 28(6): 841-856.
[36] Hunik L, Chaabouni A, van Laarhoven T, et al. Diagnostic prediction models for primary care, based on AI and electronic health records: Systematic review [J]. JMIR Medical Informatics, 2025, 13: e62862.