Literature DB >> 30243616

Digital diabetes: Perspectives for diabetes prevention, management and research.

G Fagherazzi1, P Ravaud2.   

Abstract

Digital medicine, digital research and artificial intelligence (AI) have the power to transform the field of diabetes with continuous and no-burden remote monitoring of patients' symptoms, physiological data, behaviours, and social and environmental contexts through the use of wearables, sensors and smartphone technologies. Moreover, data generated online and by digital technologies - which the authors suggest be grouped under the term 'digitosome' - constitute, through the quantity and variety of information they represent, a powerful potential for identifying new digital markers and patterns of risk that, ultimately, when combined with clinical data, can improve diabetes management and quality of life, and also prevent diabetes-related complications. Moving from a world in which patients are characterized by only a few recent measurements of fasting glucose levels and glycated haemoglobin to a world where patients, healthcare professionals and research scientists can consider various key parameters at thousands of time points simultaneously will profoundly change the way diabetes is prevented, managed and characterized in patients living with diabetes, as well as how it is scientifically researched. Indeed, the present review looks at how the digitization of diabetes can impact all fields of diabetes - its prevention, management, technology and research - and how it can complement, but not replace, what is usually done in traditional clinical settings. Such a profound shift is a genuine game changer that should be embraced by all, as it can provide solid research results transferable to patients, improve general health literacy, and provide tools to facilitate the everyday decision-making process by both healthcare professionals and patients living with diabetes.
Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  Artificial intelligence; Big data; Diabetes; Social media; Technology

Mesh:

Year:  2018        PMID: 30243616     DOI: 10.1016/j.diabet.2018.08.012

Source DB:  PubMed          Journal:  Diabetes Metab        ISSN: 1262-3636            Impact factor:   6.041


  25 in total

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Review 2.  mHealth prompts within diabetes prevention programs: a scoping review.

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Review 3.  Prevention of Type 2 Diabetes.

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Review 4.  Machine Learning and Natural Language Processing in Mental Health: Systematic Review.

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5.  Challenges of and Solutions for Developing Tailored Video Interventions That Integrate Multiple Digital Assets to Promote Engagement and Improve Health Outcomes: Tutorial.

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Review 6.  Digital Diabetes Management: A Literature Review of Smart Insulin Pens.

Authors:  Lutz Heinemann; Oliver Schnell; Bernhard Gehr; Nanette C Schloot; Sven W Görgens; Christoph Görgen
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7.  Artificial Intelligence and Big Data in Diabetes Care: A Position Statement of the Italian Association of Medical Diabetologists.

Authors:  Nicoletta Musacchio; Annalisa Giancaterini; Giacomo Guaita; Alessandro Ozzello; Maria A Pellegrini; Paola Ponzani; Giuseppina T Russo; Rita Zilich; Alberto de Micheli
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8.  Reusable, Non-Invasive, and Ultrafast Radio Frequency Biosensor Based on Optimized Integrated Passive Device Fabrication Process for Quantitative Detection of Glucose Levels.

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Journal:  Sensors (Basel)       Date:  2020-03-11       Impact factor: 3.576

9.  Meeting the Challenge of Diabetes in China.

Authors:  Zhen Luo; Guilhem Fabre; Victor G Rodwin
Journal:  Int J Health Policy Manag       Date:  2020-02-01

Review 10.  The Use of Social Media for Health Research Purposes: Scoping Review.

Authors:  Charline Bour; Adrian Ahne; Susanne Schmitz; Camille Perchoux; Coralie Dessenne; Guy Fagherazzi
Journal:  J Med Internet Res       Date:  2021-05-27       Impact factor: 5.428

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