ReviewIEEE transactions on bio-medical engineering2015
A Review of Emerging Technologies for the Management of Diabetes Mellitus.
Review in IEEE transactions on bio-medical engineering, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed.
- Better Blood Pressure Control for Stroke Patients in the ICU: A Deep Reinforcement Learning with Supervised Guidance Approach for Adaptive Infusion Rate Tuning.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- RFFE - Random Forest Fuzzy Entropy for the classification of Diabetes Mellitus.AIMS public health · 2023Article
- Effects of a Novel Blood Glucose Forecasting Feature on Glycemic Management and Logging in Adults With Type 2 Diabetes Using One Drop: Retrospective Cohort Study.JMIR diabetes · 2022Article
- A Multimodal Approach for Real Time Recognition of Engagement towards Adaptive Serious Games for Health.Sensors (Basel, Switzerland) · 2022Article
- Multi-step ahead predictive model for blood glucose concentrations of type-1 diabetic patients.Scientific reports · 2021Article
- Diabetes self-management in online health communities: an information exchange perspective.BMC medical informatics and decision making · 2021Article
- Forecasting of Glucose Levels and Hypoglycemic Events: Head-to-Head Comparison of Linear and Nonlinear Data-Driven Algorithms Based on Continuous Glucose Monitoring Data Only.Sensors (Basel, Switzerland) · 2021Article
- Design and Development of Diabetes Management System Using Machine Learning.International journal of telemedicine and applications · 2020Article
- Improving Accuracy for Diabetes Mellitus Prediction by Using Deepnet.Online journal of public health informatics · 2020Article
- User Centered Design to Improve Information Exchange in Diabetes Care Through eHealth : Results from a Small Scale Exploratory Study.Journal of medical systems · 2019Article
- Hypoglycemia Prevention via Personalized Glucose-Insulin Models Identified in Free-Living Conditions.Journal of diabetes science and technology · 2019Article
- What do healthcare professionals need to turn risk models for type 2 diabetes into usable computerized clinical decision support systems? Lessons learned from the MOSAIC project.BMC medical informatics and decision making · 2019Article
- Limits to the Evaluation of the Accuracy of Continuous Glucose Monitoring Systems by Clinical Trials.Biosensors · 2018Article
- DMTO: a realistic ontology for standard diabetes mellitus treatment.Journal of biomedical semantics · 2018Article
- Effect of acrylodan conjugation and forced oxidation on the structural integrity, conformational stability, and binding activity of a glucose binding protein SM4 used in a prototype continuous glucose monitor.Protein science : a publication of the Protein Society · 2017Article
- Non-invasive detection of fasting blood glucose level via electrochemical measurement of saliva.SpringerPlus · 2016Article
- Special issue on emerging technologies for the management of diabetes mellitus.Medical & biological engineering & computing · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
objectiveHigh prevalence of diabetes mellitus (DM) along with the poor health outcomes and the escalated costs of treatment and care poses the need to focus on prevention, early detection and improved management of the disease. The aim of this paper is to present and discuss the latest accomplishments in sensors for glucose and lifestyle monitoring along with clinical decision support systems (CDSSs) facilitating self-disease management and supporting healthcare professionals in decision making.
methodsA critical literature review analysis is conducted focusing on advances in: 1) sensors for physiological and lifestyle monitoring, 2) models and molecular biomarkers for predicting the onset and assessing the progress of DM, and 3) modeling and control methods for regulating glucose levels.
resultsGlucose and lifestyle sensing technologies are continuously evolving with current research focusing on the development of noninvasive sensors for accurate glucose monitoring. A wide range of modeling, classification, clustering, and control approaches have been deployed for the development of the CDSS for diabetes management. Sophisticated multiscale, multilevel modeling frameworks taking into account information from behavioral down to molecular level are necessary to reveal correlations and patterns indicating the onset and evolution of DM.
conclusionIntegration of data originating from sensor-based systems and electronic health records combined with smart data analytics methods and powerful user centered approaches enable the shift toward preventive, predictive, personalized, and participatory diabetes care. SIGNIFICANCE: The potential of sensing and predictive modeling approaches toward improving diabetes management is highlighted and related challenges are identified.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.