Artificial Intelligence in Diabetes Care and Prevention

Articles published in this theme: 64 (scroll down to load remaining articles)

2026

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Patient Perceptions of Artificial Intelligence in Diabetes Self-Management: Cross-Sectional Survey Study

Nataly Martini, Navneet Kaur Dhaliwal, Elena Alipour, Shane Scahill, Laszlo Sajtos

JMIR Form Res 2026 (Mar 16); 10:e83030

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Complete Blood Count–Derived Inflammation Indices to Predict 3-Year All-Cause Mortality in Patients With Diabetes and Acute Myocardial Infarction in Critical Care: Retrospective Cohort Study With Single-Center External Validation

Tong Zhou, Kun Yang, Ying Yang, Song-Mei Liu

JMIR Med Inform 2026 (Mar 12); 14:e83328

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Digital Health Solutions for Type 2 Diabetes and Prediabetes: Systematic Review of Engagement Barriers, Facilitators, and Outcomes

Ayesha Thanthrige, Nilmini Wickramasinghe

JMIR Diabetes 2026 (Mar 12); 11:e80582

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AI-Enabled Personalization of Semaglutide Therapy in Type 2 Diabetes: Systematic Review With an Integration Framework

Ghinwa Barakat, Samer El Hajj Hassan, Hanane Akhdar, Nghia Duong-Trung, Wiam Ramadan

JMIR AI 2026 (Mar 09); 5:e86960

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Using Textural Analysis of Thermal Imaging to Predict Healing Status of Diabetes-Related Neuropathic Foot Ulcers: Protocol for a Co-Design and Longitudinal Study

Kate Waller, Rajna Ogrin, Quoc Cuong Ngo, Barbara Polus, Samantha Hanna, Aye Nyein Tint, Richard J MacIsaac, Anna Galligan, Elif Ilhan Ekinci, Dinesh Kumar

JMIR Res Protoc 2026 (Feb 26); 15:e69793

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Cardiorespiratory Markers of Type 2 Diabetes: Machine Learning–Based Analysis

Flavia Maria G S A Oliveira, Sandro Muniz Cavalcanti, Michael C K Khoo

JMIR Diabetes 2026 (Feb 23); 11:e82084

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Personalized Diabetes Treatment Support Using Large Language Models Fine-Tuned on Electronic Health Records: Development and Evaluation Study

Shengyang He, Yu Zhang, Jiaxi Li

JMIR Form Res 2026 (Feb 09); 10:e71541

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Predictors of Glycemic Response to Sulfonylurea Therapy in Type 2 Diabetes Over 12 Months: Comparative Analysis of Linear Regression and Machine Learning Models

Shilpa Garg, Robert Kitchen, Ramneek Gupta, Emanuele Trucco, Ewan Pearson

JMIR Diabetes 2026 (Feb 06); 11:e82635

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Privacy-Preserving Collaborative Diabetes Prediction in Heterogeneous Health Care Systems: Algorithm Development and Validation of a Secure Federated Ensemble Framework

Md Rakibul Hasan, Juan Li

JMIR Diabetes 2026 (Jan 26); 11:e79166

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Artificial Intelligence in Diabetic Kidney Disease Research: Bibliometric Analysis From 2006 to 2024

Xingyuan Li, Liming Xiao, Fenghao Yang, Fang Liu

JMIR Diabetes 2026 (Jan 09); 11:e72616

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2025

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Artificial Intelligence–Enabled Mobile Health Intervention (mDiabetes) to Reduce Diabetes Risk Behaviors in Rural India: Quasi-Experimental Pre-Post Study

Joshua Chadwick, Nidhi Jaswal, Janani Surya, Chandru Sivamani, Varun Ramesan, Nalini Saligram

J Med Internet Res 2025 (Dec 05); 27:e79283

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AI-Powered Thermography for Diabetic Foot Risk Stratification: Multicenter Cross-Sectional Study

Meshari F Alwashmi, Mustafa alghali, Waseem Abu-Ashour, Abdullah Mohammed Arabe, Abdullah Al Soheimi, Nasibh Abdulrahman Alharbi, Hani Mohammed Badahdah

JMIR Form Res 2025 (Nov 27); 9:e81289

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Generative AI Chatbot for Diabetes Management: Formative 2-Part Qualitative Study Using DTalksBot Involving Patients and Clinicians

Soyun Jeon, Seolhee Lee, Esther Hehsun Kim, Jinsu Eun, Kwangwon Lee, Hajin Lim, Joonhwan Lee

JMIR Form Res 2025 (Nov 12); 9:e72553

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Comparison of Risk Factors, Their Interaction Patterns, and Scoring Systems for Liver Cancer Between Patients With and Those Without Diabetes: Retrospective Cohort Study Using Electronic Health Records and Tree-Structured Algorithms

Sarah Tsz Yui Yau, Chi Tim Hung, Eman Yee Man Leung, Albert Lee, Eng Kiong Yeoh

JMIR Med Inform 2025 (Oct 27); 13:e72239

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Interpretable Machine Learning Model for Predicting and Assessing the Risk of Diabetic Nephropathy: Prediction Model Study

Yili Wen, Zhiqiang Wan, Huiling Ren, Xu Wang, Weijie Wang

JMIR Med Inform 2025 (Oct 22); 13:e64979

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Evaluation of Machine Learning Model Performance in Diabetic Foot Ulcer: Retrospective Cohort Study

Veerle Y van Velze, Hendrico L Burger, Tim J van der Steenhoven, Hani Al-Ers, Lauren N Goncalves, Daniël Eefting, Willem-Jan J de Jong, Harm J Smeets, Janna C Specken Welleweerd, Joost R van der Vorst, Sandy Uchtmann, Robert Rissmann, Jaap F Hamming, Lampros Stergioulas, Koen EA van der Bogt

JMIR Med Inform 2025 (Oct 10); 13:e71994

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Use of Automated Machine Learning to Detect Undiagnosed Diabetes in US Adults: Development and Validation Study

Jianxiu Liu, Fred Ssewamala, Ruopeng An, Mengmeng Ji

JMIR AI 2025 (Oct 08); 4:e68260

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Principles and Practices of Community Engagement in AI for Population Health: Formative Qualitative Study of the AI for Diabetes Prediction and Prevention Project

Ibukun-Oluwa Omolade Abejirinde, Ijeoma Uchenna Itanyi, Kathy Kornas, Remziye Zaim, Shion Guha, Victoria Chui, Lorraine Lipscombe, Laura C Rosella, James Shaw

J Particip Med 2025 (Oct 02); 17:e69497

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Toward a Clinically Actionable, Electronic Health Record–Based Machine Learning Model to Forecast 90-Day Change in Hemoglobin A1c in Youth With Type 1 Diabetes: Feasibility and Model Development Study

Erin M Tallon, David D Williams, Cintya Schweisberger, Colin Mullaney, Brent Lockee, Diana Ferro, Craig A Vandervelden, Mitchell S Barnes, Angelica Cristello Sarteau, Anna R Kahkoska, Susana R Patton, Sanjeev Mehta, Ryan McDonough, Marcus Lind, Leonard D'Avolio, Mark A Clements

JMIR Diabetes 2025 (Sep 25); 10:e69142

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Optimizing Feature Selection and Machine Learning Algorithms for Early Detection of Prediabetes Risk: Comparative Study

Mahmoud B Almadhoun, MA Burhanuddin

JMIR Bioinform Biotech 2025 (Jul 31); 6:e70621

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