Published on in Vol 6, No 1 (2018): January

Preprints (earlier versions) of this paper are available at, first published .
Development and Evaluation of a Mobile Personalized Blood Glucose Prediction System for Patients With Gestational Diabetes Mellitus

Development and Evaluation of a Mobile Personalized Blood Glucose Prediction System for Patients With Gestational Diabetes Mellitus

Development and Evaluation of a Mobile Personalized Blood Glucose Prediction System for Patients With Gestational Diabetes Mellitus


  1. Pustozerov E, Tkachuk A, Vasukova E, Dronova A, Shilova E, Anopova A, Piven F, Pervunina T, Vasilieva E, Grineva E, Popova P. The Role of Glycemic Index and Glycemic Load in the Development of Real-Time Postprandial Glycemic Response Prediction Models for Patients with Gestational Diabetes. Nutrients 2020;12(2):302 View
  2. Wang Y, Li M, Zhao X, Pan X, Lu M, Lu J, Hu Y. Effects of continuous care for patients with type 2 diabetes using mobile health application: A randomised controlled trial. The International Journal of Health Planning and Management 2019;34(3):1025 View
  3. Pustozerov E, Chernykh V, Popova P, Vasyukova E, Tkachuk A, Yuldashev Z. Health Monitoring System for Patients with Gestational Diabetes Mellitus Based on Nutrition Diaries and Fitness Bracelets. Biomedical Engineering 2020;53(5):305 View
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  5. Popova P, Vasilyeva L, Tkachuck A, Puzanov M, Golovkin A, Bolotko Y, Pustozerov E, Vasilyeva E, Li O, Zazerskaya I, Dmitrieva R, Kostareva A, Grineva E. A Randomised, Controlled Study of Different Glycaemic Targets during Gestational Diabetes Treatment: Effect on the Level of Adipokines in Cord Blood and ANGPTL4 Expression in Human Umbilical Vein Endothelial Cells. International Journal of Endocrinology 2018;2018:1 View
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  10. Surendran S, Lim C, Koh G, Yew T, Tai E, Foong P. Women’s Usage Behavior and Perceived Usefulness with Using a Mobile Health Application for Gestational Diabetes Mellitus: Mixed-Methods Study. International Journal of Environmental Research and Public Health 2021;18(12):6670 View
  11. Shang J, Henry A, Zhang P, Chen H, Thompson K, Wang X, Liu N, Zhang J, Liu Y, Jin J, Pan X, Yang X, Hirst J. Chinese women’s attitudes towards postpartum interventions to prevent type 2 diabetes after gestational diabetes: a semi-structured qualitative study. Reproductive Health 2021;18(1) View
  12. De Croon R, Van Houdt L, Htun N, Štiglic G, Vanden Abeele V, Verbert K. Health Recommender Systems: Systematic Review. Journal of Medical Internet Research 2021;23(6):e18035 View
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  16. Napolsky I, Popova P. Personalized Nutrition for the Prevention and Treatment of Metabolic Diseases: Opportunities and Perspectives. Russian Journal for Personalized Medicine 2022;2(1):15 View
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  24. Rivera-Romero O, Gabarron E, Ropero J, Denecke K. Designing personalised mHealth solutions: An overview. Journal of Biomedical Informatics 2023;146:104500 View
  25. Popova P, Anopova A, Vasukova E, Isakov A, Eriskovskaya A, Degilevich A, Pustozerov E, Tkachuk A, Pashkova K, Krasnova N, Kokina M, Nemykina I, Pervunina T, Li O, Grineva E, Shlyakhto E. Trial protocol for the study of recommendation system DiaCompanion with personalized dietary recommendations for women with gestational diabetes mellitus (DiaCompanion I). Frontiers in Endocrinology 2023;14 View
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  27. Lu H, Lu P, Hirst J, Mackillop L, Clifton D. A Stacked Long Short-Term Memory Approach for Predictive Blood Glucose Monitoring in Women with Gestational Diabetes Mellitus. Sensors 2023;23(18):7990 View
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Books/Policy Documents

  1. Pustozerov E, Sachkova N, Tkachuk A, Vasukova E, Dronova A, Pervunina T, Grineva E, Popova P. International Youth Conference on Electronics, Telecommunications and Information Technologies. View
  2. Xanthis C, Filos D, Chouvarda I. Comprehensive Clinical Approach to Diabetes During Pregnancy. View