当前位置： SCI文献检索 > IEEE Journal of Biomedical and Health Informatics期刊下所有文献 > Advanced Insulin Bolus Advisor Based on Run-To-Run Control and Case-Based Reasoning.

Advanced Insulin Bolus Advisor Based on Run-To-Run Control and Case-Based Reasoning.

Abstract：

:This paper presents an advanced insulin bolus advisor for people with diabetes on multiple daily injections or insulin pump therapy. The proposed system, which runs on a smartphone, keeps the simplicity of a standard bolus calculator while enhancing its performance by providing more adaptability and flexibility. This is achieved by means of applying a retrospective optimization of the insulin bolus therapy using a novel combination of run-to-run (R2R) that uses intermittent continuous glucose monitoring data, and case-based reasoning (CBR). The validity of the proposed approach has been proven by in-silico studies using the FDA-accepted UVa-Padova type 1 diabetes simulator. Tests under more realistic in-silico scenarios are achieved by updating the simulator to emulate intrasubject insulin sensitivity variations and uncertainty in the capillarity measurements and carbohydrate intake. The CBR(R2R) algorithm performed well in simulations by significantly reducing the mean blood glucose, increasing the time in euglycemia and completely eliminating hypoglycaemia. Finally, compared to an R2R stand-alone version of the algorithm, the CBR(R2R) algorithm performed better in both adults and adolescent populations, proving the benefit of the utilization of CBR. In particular, the mean blood glucose improved from 166 ± 39 to 150 ± 16 in the adult populations (p = 0.03) and from 167 ± 25 to 162 ± 23 in the adolescent population (p = 0.06). In addition, CBR(R2R) was able to completely eliminate hypoglycaemia, while the R2R alone was not able to do it in the adolescent population.

journal_name

IEEE J Biomed Health Inform

journal_title

IEEE journal of biomedical and health informatics

authors

Herrero P,Pesl P,Reddy M,Oliver N,Georgiou P,Toumazou C

doi

10.1109/JBHI.2014.2331896

subject

Has Abstract

pub_date

2015-05-01 00:00:00

pages

1087-96

issue

3

eissn

2168-2194

issn

2168-2208

journal_volume

19

pub_type

杂志文章

相关文献

IEEE Journal of Biomedical and Health Informatics文献大全
  • A DNA-Based Intelligent Expert System for Personalised Skin-Health Recommendations.

    abstract：:Intensive attention on personalised skin-health solutions is on account of incomparable love of skin and an urgent need for effective treatment. In the meanwhile, people have great expectations on how to utilise genetic knowledge of our body to provide a precise solution for different individuals, such as daily use of...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.2978667

    authors： Liu X,Chen CH,Karvela M,Toumazou C

    更新日期：2020-11-01 00:00:00

  • Wireless gigabit data telemetry for large-scale neural recording.

    abstract：:Implantable wireless neural recording from a large ensemble of simultaneously acting neurons is a critical component to thoroughly investigate neural interactions and brain dynamics from freely moving animals. Recent researches have shown the feasibility of simultaneously recording from hundreds of neurons and suggest...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2015.2416202

    authors： Kuan YC,Lo YK,Kim Y,Chang MC,Liu W

    更新日期：2015-05-01 00:00:00

  • A Global Covariance Descriptor for Nuclear Atypia Scoring in Breast Histopathology Images.

    abstract：:Nuclear atypia scoring is a diagnostic measure commonly used to assess tumor grade of various cancers, including breast cancer. It provides a quantitative measure of deviation in visual appearance of cell nuclei from those in normal epithelial cells. In this paper, we present a novel image-level descriptor for nuclear...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2015.2447008

    authors： Khan AM,Sirinukunwattana K,Rajpoot N

    更新日期：2015-09-01 00:00:00

  • Automatic Analysis of Food Intake and Meal Microstructure Based on Continuous Weight Measurements.

    abstract：:The structure of the cumulative food intake (CFI) curve has been associated with obesity and eating disorders. Scales that record the weight loss of a plate from which a subject eats food are used for capturing this curve; however, their measurements are contaminated by additive noise and are distorted by certain type...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2018.2812243

    authors： Papapanagiotou V,Diou C,Ioakimidis I,Sodersten P,Delopoulos A

    更新日期：2019-03-01 00:00:00

  • A novel and lightweight system to secure wireless medical sensor networks.

    abstract：:Wireless medical sensor networks (MSNs) are a key enabling technology in e-healthcare that allows the data of a patient's vital body parameters to be collected by the wearable or implantable biosensors. However, the security and privacy protection of the collected data is a major unsolved issue, with challenges coming...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2013.2268897

    authors： He D,Chan S,Tang S

    更新日期：2014-01-01 00:00:00

  • Deep Learning for Health Informatics.

    abstract：:With a massive influx of multimodality data, the role of data analytics in health informatics has grown rapidly in the last decade. This has also prompted increasing interests in the generation of analytical, data driven models based on machine learning in health informatics. Deep learning, a technique with its founda...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章,评审

    doi：10.1109/JBHI.2016.2636665

    authors： Ravi D,Wong C,Deligianni F,Berthelot M,Andreu-Perez J,Lo B,Yang GZ

    更新日期：2017-01-01 00:00:00

  • Unsupervised eye blink artifact denoising of EEG data with modified multiscale sample entropy, Kurtosis, and wavelet-ICA.

    abstract：:Brain activities commonly recorded using the electroencephalogram (EEG) are contaminated with ocular artifacts. These activities can be suppressed using a robust independent component analysis (ICA) tool, but its efficiency relies on manual intervention to accurately identify the independent artifactual components. In...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2014.2333010

    authors： Mahajan R,Morshed BI

    更新日期：2015-01-01 00:00:00

  • Optimized Multistable Stochastic Resonance for the Enhancement of Pituitary Microadenoma in MRI.

    abstract：:Magnetic resonance imaging (MRI) is the modality of choice as far as imaging diagnosis of pathologies in the pituitary gland is concerned. Furthermore, the advent of dynamic contrast enhanced (DCE) has enhanced the capability of this modality in detecting minute benign but endocrinologically significant tumors called ...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2017.2715078

    authors： Singh M,Verma A,Sharma N

    更新日期：2018-05-01 00:00:00

  • An Attribute Supervised Probabilistic Dependent Matrix Tri-Factorization Model for the Prediction of Adverse Drug-Drug Interaction.

    abstract：:Adverse drug-drug interaction (ADDI) becomes a significant threat to public health. Despite the detection of ADDIs is experimentally implemented in the early development phase of drug design, many potential ADDIs are still clinically explored by accidents, leading to a large number of morbidity and mortality. Several ...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.3048059

    authors： Zhu J,Liu Y,Zhang Y,Li D

    更新日期：2020-12-29 00:00:00

  • Synchronization and Registration of Cine Magnetic Resonance and Dynamic Computed Tomography Images of the Heart.

    abstract：:The synchronization and registration of dynamic computed tomography (CT) and magnetic resonance images (MRI) of the heart is required to perform a combined analysis of their complementary information. We propose a novel method that synchronizes and registers intrapatient dynamic CT and cine-MRI short axis view (SAX). ...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2015.2453639

    authors： Betancur J,Simon A,Langella B,Leclercq C,Hernandez A,Garreau M

    更新日期：2016-09-01 00:00:00

  • Simultaneous Clustering and Feature Weighting Using Multiobjective Optimization for Identifying Functionally Similar miRNAs.

    abstract：:MicroRNAs (miRNAs) are a type of RNAs, which are responsible for monitoring the gene expression values. Recent research asserts that miRNAs form some clustering on chromosomes. The miRNAs belonging to a particular cluster are highly similar in terms of their activity and they are termed as "coregulated" miRNAs. The cu...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2017.2784898

    authors： Saha S,Acharya S,K K,Miriyala S

    更新日期：2018-09-01 00:00:00

  • Multi-Scale Time-Series Kernel-Based Learning Method for Brain Disease Diagnosis.

    abstract：:The functional magnetic resonance imaging (fMRI) is a noninvasive technique for studying brain activity, such as brain network analysis, neural disease automated diagnosis and so on. However, many existing methods have some drawbacks, such as limitations of graph theory, lack of global topology characteristic, local s...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.2983456

    authors： Zhang Z,Ding J,Xu J,Tang J,Guo F

    更新日期：2021-01-01 00:00:00

  • Design comorbidity portfolios to improve treatment cost prediction of asthma using machine learning.

    abstract：:Comorbidity is an important factor to consider when trying to predict the cost of treating asthma patients. When an asthmatic patient suffered from comorbidity, the cost of treating such a patient becomes dependent on the nature of the comorbidity. Therefore, lack of recognition of comorbidity on asthmatic patient pos...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.3034092

    authors： Luo L,Yu X,Yong Z,Li C,Gu Y

    更新日期：2020-10-27 00:00:00

  • Performance Analysis of Gyroscope and Accelerometer Sensors for Seismocardiography-Based Wearable Pre-Ejection Period Estimation.

    abstract：OBJECTIVE:Systolic time intervals, such as the pre-ejection period (PEP), are important parameters for assessing cardiac contractility that can be measured non-invasively using seismocardiography (SCG). Recent studies have shown that specific points on accelerometer- and gyroscope-based SCG signals can be used for PEP ...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2019.2895775

    authors： Shandhi MMH,Semiz B,Hersek S,Goller N,Ayazi F,Inan OT

    更新日期：2019-11-01 00:00:00

  • cuProCell: GPU-Accelerated Analysis of Cell Proliferation With Flow Cytometry Data.

    abstract：:The investigation of cell proliferation can provide useful insights for the comprehension of cancer progression, resistance to chemotherapy and relapse. To this aim, computational methods and experimental measurements based on in vivo label-retaining assays can be coupled to explore the dynamic behavior of tumoral cel...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.3005423

    authors： Nobile MS,Nisoli E,Vlachou T,Spolaor S,Cazzaniga P,Mauri G,Pelicci PG,Besozzi D

    更新日期：2020-11-01 00:00:00

  • Cluster-based analysis for personalized stress evaluation using physiological signals.

    abstract：:Technology development in wearable sensors and biosignal processing has made it possible to detect human stress from the physiological features. However, the intersubject difference in stress responses presents a major challenge for reliable and accurate stress estimation. This research proposes a novel cluster-based ...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章,随机对照试验

    doi：10.1109/JBHI.2014.2311044

    authors： Xu Q,Nwe TL,Guan C

    更新日期：2015-01-01 00:00:00

  • Laryngeal Tumor Detection and Classification in Endoscopic Video.

    abstract：:The development of the narrow-band imaging (NBI) has been increasing the interest of medical specialists in the study of laryngeal microvascular network to establish diagnosis without biopsy and pathological examination. A possible solution to this challenging problem is presented in this paper, which proposes an auto...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2014.2374975

    authors： Barbalata C,Mattos LS

    更新日期：2016-01-01 00:00:00

  • Coronary vein extraction in MSCT volumes using minimum cost path and geometrical moments.

    abstract：:This work deals with the extraction of patient-specific coronary venous anatomy in preoperative multislice computed tomography (MSCT) volumes. A hybrid approach has been specifically designed for low-contrast vascular structure detection. It makes use of a minimum cost path technique with a Fast-Marching front propaga...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2013.2245420

    authors： Garcia MP,Velut J,Boulmier D,Leclercq C,Garreau M,Haigron P,Toumoulin C

    更新日期：2013-03-01 00:00:00

  • Estimation of Circadian Body Temperature Rhythm Based on Heart Rate in Healthy, Ambulatory Subjects.

    abstract：:Core body temperature is a reliable marker for circadian rhythm. As characteristics of the circadian body temperature rhythm change during diverse health problems, such as sleep disorder and depression, body temperature monitoring is often used in clinical diagnosis and treatment. However, the use of current thermomet...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2016.2529655

    authors： Sim SY,Joo KM,Kim HB,Jang S,Kim B,Hong S,Kim S,Park KS

    更新日期：2017-03-01 00:00:00

  • A Fuzzy Kernel Motion Classifier for Autonomous Stroke Rehabilitation.

    abstract：:Autonomous poststroke rehabilitation systems which can be deployed outside hospital with no or reduced supervision have attracted increasing amount of research attentions due to the high expenditure associated with the current inpatient stroke rehabilitation systems. To realize an autonomous systems, a reliable patien...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2015.2430524

    authors： Zhang Z,Liparulo L,Panella M,Gu X,Fang Q

    更新日期：2016-05-01 00:00:00

  • LMI-Based Approaches for the Calibration of Continuous Glucose Measurement Sensors.

    abstract：:The problem of online calibration and recalibration of continuous glucose monitoring (CGM) devices is considered. Two different parametric relations between interstitial and blood glucose are investigated and constructive algorithms to adaptively estimate the parameters within those relations are proposed. One charact...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2014.2341703

    authors： Kirchsteiger H,Zaccarian L,Renard E,del Re L

    更新日期：2015-09-01 00:00:00

  • Inaccurate Labels in Weakly-Supervised Deep Learning: Automatic Identification and Correction and Their Impact on Classification Performance.

    abstract：:In data-driven deep learning-based modeling, data quality may substantially influence classification performance. Correct data labeling for deep learning modeling is critical. In weakly-supervised learning, a challenge lies in dealing with potentially inaccurate or mislabeled training data. In this paper, we proposed ...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.2974425

    authors： Hao D,Zhang L,Sumkin J,Mohamed A,Wu S

    更新日期：2020-09-01 00:00:00

  • AW-SDRLSE: Adaptive Weighting and Scalable Distance Regularized Level Set Evolution for Lymphoma Segmentation on PET Images.

    abstract：:Accurate lymphoma segmentation on Positron Emission Tomography (PET) images is of great importance for medical diagnoses, such as for distinguishing benign and malignant. To this end, this paper proposes an adaptive weighting and scalable distance regularized level set evolution (AW-SDRLSE) method for delineating lymp...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.3017546

    authors： Li S,Jiang H,Li H,Yao YD

    更新日期：2020-08-25 00:00:00

  • A Multidimensional Time-Series Similarity Measure With Applications to Eldercare Monitoring.

    abstract：:In the last decade, data mining techniques have been applied to sensor data in a wide range of application domains, such as healthcare monitoring systems, manufacturing processes, intrusion detection, database management, and others. Many data mining techniques are based on computing the similarity between two sensor ...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2015.2424711

    authors： Hajihashemi Z,Popescu M

    更新日期：2016-05-01 00:00:00

  • Bi-Frequency Symmetry Difference EIT-Feasibility and Limitations of Application to Stroke Diagnosis.

    abstract：OBJECTIVE:Bi-Frequency Symmetry Difference (BFSD)-EIT can detect, localize and identify unilateral perturbations in symmetric scenes. Here, we test the viability and robustness of BFSD-EIT in stroke diagnosis. METHODS:A realistic 4-layer Finite Element Method (FEM) head model with and without bleed and clot lesions is...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2019.2960862

    authors： McDermott B,O'Halloran M,Avery J,Porter E

    更新日期：2020-08-01 00:00:00

  • Improved semisupervised adaptation for a small training dataset in the brain-computer interface.

    abstract：:One problem in the development of brain-computer interface (BCI) systems is to minimize the amount of subject training on the premise of accurate classification. Hence, the challenge is how to train the BCI system effectively especially in the scenario with small amount of training data. In this paper, we introduce im...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2013.2285232

    authors： Meng J,Sheng X,Zhang D,Zhu X

    更新日期：2014-07-01 00:00:00

  • GP-CNN-DTEL: Global-Part CNN Model With Data-Transformed Ensemble Learning for Skin Lesion Classification.

    abstract：:Precise skin lesion classification is still challenging due to two problems, i.e., (1) inter-class similarity and intra-class variation of skin lesion images, and (2) the weak generalization ability of single Deep Convolutional Neural Network trained with limited data. Therefore, we propose a Global-Part Convolutional...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.2977013

    authors： Tang P,Liang Q,Yan X,Xiang S,Zhang D

    更新日期：2020-10-01 00:00:00

  • ELEMENT: Multi-Modal Retinal Vessel Segmentation Based on a Coupled Region Growing and Machine Learning Approach.

    abstract：:Vascular structures in the retina contain important information for the detection and analysis of ocular diseases, including age-related macular degeneration, diabetic retinopathy and glaucoma. Commonly used modalities in diagnosis of these diseases are fundus photography, scanning laser ophthalmoscope (SLO) and fluor...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.2999257

    authors： Rodrigues EO,Conci A,Liatsis P

    更新日期：2020-12-01 00:00:00

  • Multi-Hypergraph Learning for Incomplete Multimodality Data.

    abstract：:Multi-modality data convey complementary information that can be used to improve the accuracy of prediction models in disease diagnosis. However, effectively integrating multi-modality data remains a challenging problem, especially when the data are incomplete. For instance, more than half of the subjects in the Alzhe...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2017.2732287

    authors： Liu M,Gao Y,Yap PT,Shen D

    更新日期：2018-07-01 00:00:00

  • Automatic motion analysis system for pyloric flow in ultrasonic videos.

    abstract：:Ultrasonography has been widely used to evaluate duodenogastric reflux (DGR). But to the best of our knowledge, no automatic analysis system was developed to realize the quantitative computer-aided analysis. In this paper, we propose a system to perform the automatic detection of DGR in the ultrasonic image sequences ...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2013.2272090

    authors： Chen C,Wang Y,Yu J,Zhou Z,Shen L,Chen YQ

    更新日期：2014-01-01 00:00:00