4.7 Article

Hypoglycaemia prediction using information fusion and classifiers consensus

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Computer Science, Interdisciplinary Applications

Information fusion and multi-classifier system for miner fatigue recognition in plateau environments based on electrocardiography and electromyography signals

Shoukun Chen et al.

Summary: This study demonstrates that using machine learning models such as SVM, RF, and XG-Boost can effectively identify fatigue in miners working under extreme conditions. The PCA fusion technique outperforms the GRA method in improving identification accuracy, with XG-Boost classification yielding the best accuracy and robustness.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2021)

Review Chemistry, Analytical

Machine Learning Techniques for Hypoglycemia Prediction: Trends and Challenges

Omer Mujahid et al.

Summary: The use of machine learning techniques in predicting hypoglycemia has been increasing in recent years for diabetic patients to anticipate and intervene in potential hypoglycemic events, improving their quality of life. The review identified a split between hypoglycemia prediction and detection works categorized based on machine learning approaches, training data, and prediction horizon.

SENSORS (2021)

Article Endocrinology & Metabolism

Risk prediction for severe hypoglycemia in a type 2 diabetes population with previous non-severe hypoglycemia

Anita D. Misra-Hebert et al.

JOURNAL OF DIABETES AND ITS COMPLICATIONS (2020)

Article Engineering, Biomedical

Blood glucose prediction model for type 1 diabetes based on artificial neural network with time-domain features

Ganjar Alfian et al.

BIOCYBERNETICS AND BIOMEDICAL ENGINEERING (2020)

Article Computer Science, Information Systems

Prediction of Adverse Glycemic Events From Continuous Glucose Monitoring Signal

Matteo Gadaleta et al.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2019)

Article Computer Science, Information Systems

An ARIMA Model With Adaptive Orders for Predicting Blood Glucose Concentrations and Hypoglycemia

Jun Yang et al.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2019)

Article Computer Science, Information Systems

Risk-based postprandial hypoglycemia forecasting using supervised learning

Silvia Oviedo et al.

INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS (2019)

Article Computer Science, Information Systems

A Multi-Patient Data-Driven Approach to Blood of Glucose Prediction

Alessandro Aliberti et al.

IEEE ACCESS (2019)

Article Automation & Control Systems

Model-fusion-based online glucose concentration predictions in people with type 1 diabetes

Xia Yu et al.

CONTROL ENGINEERING PRACTICE (2018)

Article Endocrinology & Metabolism

Predicting the 6-mon thrisk of severe hypoglycemia among adults with diabetes: Development and external validation of a prediction model

Emily B. Schroeder et al.

JOURNAL OF DIABETES AND ITS COMPLICATIONS (2017)

Article Health Care Sciences & Services

Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods

J. Ignacio Hidalgo et al.

JOURNAL OF MEDICAL SYSTEMS (2017)

Review Endocrinology & Metabolism

Continuous Glucose Monitoring: A Review of Recent Studies Demonstrating Improved Glycemic Outcomes

David Rodbard

DIABETES TECHNOLOGY & THERAPEUTICS (2017)

Article Automation & Control Systems

Missing Data Imputation Toolbox for MATLAB

Abel Folch-Fortuny et al.

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2016)

Article Computer Science, Interdisciplinary Applications

Prediction of nocturnal hypoglycemia by an aggregation of previously known prediction approaches: proof of concept for clinical application

Pavlo Tkachenko et al.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2016)

Article Automation & Control Systems

A Nonlinear Blind Identification Approach to Modeling of Diabetic Patients

C. Novara et al.

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY (2016)

Article Computer Science, Interdisciplinary Applications

IntelliHealth: A medical decision support application using a novel weighted multi-layer classifier ensemble framework

Saba Bashir et al.

JOURNAL OF BIOMEDICAL INFORMATICS (2016)

Article Computer Science, Interdisciplinary Applications

HMV: A medical decision support framework using multi-layer classifiers for disease prediction

Saba Bashir et al.

JOURNAL OF COMPUTATIONAL SCIENCE (2016)

Article Computer Science, Information Systems

Smartphone-based personalized blood glucose prediction

Juan Li et al.

ICT EXPRESS (2016)

Article Computer Science, Interdisciplinary Applications

Evaluation of short-term predictors of glucose concentration in type 1 diabetes combining feature ranking with regression models

Eleni I. Georga et al.

MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING (2015)

Article Computer Science, Interdisciplinary Applications

Comparative assessment of glucose prediction models for patients with type 1 diabetes mellitus applying sensors for glucose and physical activity monitoring

K. Zarkogianni et al.

MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING (2015)

Article Computer Science, Artificial Intelligence

DE2: Dynamic ensemble of ensembles for learning nonstationary data

Xu-Cheng Yin et al.

NEUROCOMPUTING (2015)

Article Neurosciences

Ensemble sparse classification of Alzheimer's disease

Manhua Liu et al.

NEUROIMAGE (2012)

Review Biochemical Research Methods

A Review of Ensemble Methods in Bioinformatics

Pengyi Yang et al.

CURRENT BIOINFORMATICS (2010)

Article Multidisciplinary Sciences

Comparison of Classifier Fusion Methods for Predicting Response to Anti HIV-1 Therapy

Andre Altmann et al.

PLOS ONE (2008)