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期刊名:Jmir diabetes

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ISSN:2371-4379

e-ISSN:2371-4379

IF/分区:2.6/Q2

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共收录本刊相关文章索引341
Clinical Trial Case Reports Meta-Analysis RCT Review Systematic Review
Classical Article Case Reports Clinical Study Clinical Trial Clinical Trial Protocol Comment Comparative Study Editorial Guideline Letter Meta-Analysis Multicenter Study Observational Study Randomized Controlled Trial Review Systematic Review
Ayesha Thanthrige,Nilmini Wickramasinghe Ayesha Thanthrige
Background: Digital health interventions, including artificial intelligence (AI)-driven solutions, offer promise for type 2 diabetes mellitus (T2DM) and prediabetes management through enhanced self-management, adherence, ...
Yun Xie,Ao Zhang,Ying Wang et al. Yun Xie et al.
Background: Patients with diabetes carry a 1.5- to 2-fold higher risk of community-acquired pneumonia (CAP) and experience more severe outcomes, yet the mechanisms that integrate metabolic dysregulation, pathogen shifts, ...
Flavia Maria G S A Oliveira,Sandro Muniz Cavalcanti,Michael C K Khoo Flavia Maria G S A Oliveira
Background: The global prevalence of type 2 diabetes mellitus (T2DM) poses significant challenges due to its association with increased cardiovascular risk and complications like cardiovascular autonomic neuropathy. Measu...
Lisa Whitehead,Min Zhang,Wai Hang Kwok et al. Lisa Whitehead et al.
Background: Culturally and linguistically diverse (CaLD) populations are at a higher risk of developing prediabetes; however, the effectiveness and implementation of digital health interventions for prediabetes management...
Gareth J Dunseath,Stephen D Luzio,Wai Yee Cheung et al. Gareth J Dunseath et al.
Background: The 75-g oral glucose tolerance test (OGTT) remains the optimal diagnostic test for use in pregnancy but needs to be performed in the clinical setting. The GTT@home OGTT device offers the potential to enable p...
Ploypun Narindrarangkura,Siroj Dejhansathit,Uzma Khan et al. Ploypun Narindrarangkura et al.
Background: Older adults with diabetes frequently access their electronic health record (EHR) notes but often report difficulty understanding medical jargon and nonspecific self-care instructions. To address this communic...
Shilpa Garg,Robert Kitchen,Ramneek Gupta et al. Shilpa Garg et al.
Background: Sulfonylureas are commonly prescribed for managing type 2 diabetes, yet treatment responses vary significantly among individuals. Although advances in machine learning (ML) may enhance predictive capabilities ...
Devi Gurung States Devi Gurung States
Background: In the past decade, telehealth has transformed health care delivery by allowing patients more rapid and convenient access to necessary care without the cost and logistical challenges of traveling to a health c...
Mercia Napame,Sylvie Picard,Tony Foglia et al. Mercia Napame et al.
Background: Closed-loop insulin delivery is the new standard of care for patients with type 1 diabetes (T1D). However, in France, its implementation remains predominantly hospital based. Expanding access to this treatment...
Md Rakibul Hasan,Juan Li Md Rakibul Hasan
Background: Diabetes prediction requires accurate, privacy-preserving, and scalable solutions. Traditional machine learning models rely on centralized data, posing risks to data privacy and regulatory compliance. Moreover...