A Predictive Model-Based Decision Support System for Diabetes Patient Empowerment-Reference-Cited by-同舟云学术

A Predictive Model-Based Decision Support System for Diabetes Patient Empowerment

Published:2021-05-27 Issue: Volume: Page:
ISSN:0926-9630
Container-title:Studies in Health Technology and Informatics
language:
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Author:

Glachs Dietmar¹,Namli Tuncay²,Strohmeier Felix¹,Rodríguez Suárez Gustavo³,Sluis Michel⁴,Delgado-Lista Javier⁵,Sont Jacob K.⁶,de Graaf Albert A.⁷,Salzsieder Eckhard⁸,Vogt Lutz⁸

Affiliation:

1. Salzburg Research Forschungsgesellschaft, Salzburg, Austria

2. Software Research & Development and Consultancy Corp., Ankara, Turkey

3. iHealthLabs EUROPE SAS, Paris, France

4. Prime Vision, Delft, Netherlands

5. Servicio Andaluz de Salud or Andalusian Health Service, Cordoba, Spain

6. Leiden University Medical Center, Leiden, Netherlands

7. Dep. Risk Analysis for Products in Development, TNO, Utrecht, Netherlands

8. Institute of Diabetes “Gerhard Katsch” Karlsburg, Karlsburg, Germany

Abstract

The main objective of POWER2DM is to develop and validate a personalized self-management support system (SMSS) for T1 and T2 diabetes patients that combines and integrates i) a decision support system (DSS) based on leading European predictive personalized models for diabetes interlinked with predictive computer models, ii) automated e-coaching functionalities based on Behavioral Change Theories, and iii) real-time Personal Data processing and interpretation. The SMSS offers a guided workflow based on treatment goals and activities where a periodic review evaluates the patients progress and provides detailed feedback on how to improve towards a healthier, diabetes appropriate lifestyle.

Publisher

IOS Press

Link

https://ebooks.iospress.nl/pdf/doi/10.3233/SHTI210321

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Critical comments regarding the assessment of quality of life and the clinical impact of the POWER2DM intervention. Reply to Pouwer F, Deschênes SS [letter];Diabetologia;2024-03-01

2. Diabetes and artificial intelligence beyond the closed loop: a review of the landscape, promise and challenges;Diabetologia;2023-11-18

3. Clinical impact of an integrated e-health system for diabetes self-management support and shared decision making (POWER2DM): a randomised controlled trial;Diabetologia;2023-09-29

4. A simple modeling framework for prediction in the human glucose–insulin system;Chaos: An Interdisciplinary Journal of Nonlinear Science;2023-07-01

5. 360° Diagnostic Tool to Personalize Lifestyle Advice in Primary Care for People With Type 2 Diabetes: Development and Usability Study;JMIR Formative Research;2023-03-07