听力与言语-语言病理学

行为科学

医学伦理学

你正在浏览IEEE Journal of Biomedical and Health Informatics期刊下所有文献
  • Segmenting Vitiligo on Clinical Face Images using CNN Trained on Synthetic and Internet Images.

    abstract::Accurately diagnosing and describing the severity of vitiligo is crucial for prognostication, treatment selection and comparison. Currently, disease severity scores require dermatologists to estimate percentage area of involvement, which is subjected to inter and intra-assessor variability. Previous studies focus on p...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2021.3055213

    authors: Li Y,Kong A,Thng S

    更新日期:2021-01-29 00:00:00

  • A Visually Interpretable Deep Learning Framework for Histopathological Image-based Skin Cancer Diagnosis.

    abstract::Owing to the high incidence rate and the severe impact of skin cancer, the precise diagnosis of malignant skin tumors is a significant goal, especially considering treatment is normally effective if the tumor is detected early. Limited published histopathological image sets and the lack of an intuitive correspondence ...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2021.3052044

    authors: Jiang S,Li H,Jin Z

    更新日期:2021-01-15 00:00:00

  • PulseGAN: Learning to generate realistic pulse waveforms in remote photoplethysmography.

    abstract::Remote photoplethysmography (rPPG) is a non-contact technique for measuring cardiac signals from facial videos. High-quality rPPG pulse signals are urgently demanded in many fields, such as health monitoring and emotion recognition. However, most of the existing rPPG methods can only be used to get average heart rate ...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2021.3051176

    authors: Song R,Chen H,Cheng J,Li C,Liu Y,Chen X

    更新日期:2021-01-12 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

  • Classification of Opioid Usage Through Semi-Supervised Learning for Total Joint Replacement Patients.

    abstract::Opioid misuse and overdose have become a public health hazard and caused drug addiction and death in the United States due to rapid increase in prescribed and non-prescribed opioid usage. The misuse and overdose are highly related to opioid over-prescription for chronic and acute pain treatment, where a one-size-fits-...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.2992973

    authors: Lee S,Wei S,White V,Bain PA,Baker C,Li J

    更新日期:2021-01-01 00:00:00

  • Adaptive Stimulation Profiles Modulation for Foot Drop Correction Using Functional Electrical Stimulation: A Proof of Concept Study.

    abstract::Functional electrical stimulation (FES) provides an effective way for foot drop (FD) correction. To overcome the redundant and blind stimulation problems in the state-of-the-art methods, this study proposes a closed-loop scheme for an adaptive electromyography (EMG)-modulated stimulation profile. The developed method ...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.2989747

    authors: Li Y,Yang X,Zhou Y,Chen J,Du M,Yang Y

    更新日期:2021-01-01 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

  • Neonatal Heart and Lung Sound Quality Assessment for Robust Heart and Breathing Rate Estimation for telehealth Applications.

    abstract::With advances in digital stethoscopes, internet of things, signal processing and machine learning, chest sounds can be easily collected and transmitted to the cloud for remote monitoring and diagnosis. However, low quality of recordings complicates remote monitoring and diagnosis, particularly for neonatal care. This ...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.3047602

    authors: Grooby E,He J,Kiewsky J,Fattahi D,Zhou L,King A,Ramanathan A,Malhotra A,Dumont GA,Marzbanrad F

    更新日期:2020-12-28 00:00:00

  • Single-stage intake gesture detection using CTC loss and extended prefix beam search.

    abstract::Accurate detection of individual intake gestures is a key step towards automatic dietary monitoring. Both inertial sensor data of wrist movements and video data depicting the upper body have been used for this purpose. The most advanced approaches to date use a two-stage approach, in which (i) framelevel intake probab...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.3046613

    authors: Rouast PV,Adam M

    更新日期:2020-12-23 00:00:00

  • DR-GAN: Conditional Generative Adversarial Network for Fine-Grained Lesion Synthesis on Diabetic Retinopathy Images.

    abstract::Diabetic retinopathy (DR) is a complication of diabetes that severely affects eyes. It can be graded into five levels of severity according to international protocol. However, optimizing a grading model to have strong generalizability requires a large amount of balanced training data, which is difficult to collect, pa...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.3045475

    authors: Zhou Y,Wang B,He X,Cui S,Shao L

    更新日期:2020-12-17 00:00:00

  • Tear Film Classification in Interferometry Eye Images Using Phylogenetic Diversity Indexes and Ripley's K Function.

    abstract::Dry eye syndrome is one of the most frequently reported eye diseases in ophthalmological practice. The diagnosis of this disease is a challenging task due to its multifactorial etiology. One of the most applied tests is the manual classification of tear film images captured with the Doane interferometer. The interfere...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.3026940

    authors: da Cruz LB,Souza JC,de Paiva AC,de Almeida JDS,Junior GB,Aires KRT,Silva AC,Gattass M

    更新日期:2020-12-01 00:00:00

  • Cooperative Low-Rank Models for Removing Stripe Noise From OCTA Images.

    abstract::Optical coherence tomography angiography (OCTA) is an emerging non-invasive imaging technique for imaging the microvasculature of the eye based on phase variance or amplitude decorrelation derived from repeated OCT images of the same tissue area. Stripe noise occurs during the OCTA acquisition process due to the invol...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.2997381

    authors: Wu X,Gao D,Borroni D,Madhusudhan S,Jin Z,Zheng Y

    更新日期:2020-12-01 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

  • Attention-Guided 3D-CNN Framework for Glaucoma Detection and Structural-Functional Association Using Volumetric Images.

    abstract::The direct analysis of 3D Optical Coherence Tomography (OCT) volumes enables deep learning models (DL) to learn spatial structural information and discover new bio-markers that are relevant to glaucoma. Downsampling 3D input volumes is the state-of-art solution to accommodate for the limited number of training volumes...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.3001019

    authors: George Y,Antony BJ,Ishikawa H,Wollstein G,Schuman JS,Garnavi R

    更新日期:2020-12-01 00:00:00

  • How to Extract More Information With Less Burden: Fundus Image Classification and Retinal Disease Localization With Ophthalmologist Intervention.

    abstract::Image classification using convolutional neural networks (CNNs) outperforms other state-of-the-art methods. Moreover, attention can be visualized as a heatmap to improve the explainability of results of a CNN. We designed a framework that can generate heatmaps reflecting lesion regions precisely. We generated initial ...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.3011805

    authors: Meng Q,Hashimoto Y,Satoh S

    更新日期:2020-12-01 00:00:00

  • Activation of Superficial and Deep Finger Flexors through Transcutaneous Nerve Stimulation.

    abstract:OBJECTIVE:Functional electrical stimulation (FES) is a common technique to elicit muscle contraction and help improve muscle strength. Traditional FES over the muscle belly typically only activates superficial muscle regions. In the case of hand FES, this prevents the activation of the deeper flexor muscles which contr...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.3041669

    authors: Shin H,Hawari MA,Hu X

    更新日期:2020-12-01 00:00:00

  • Screening For Depression With Retrospectively Harvested Private Versus Public Text.

    abstract::Depression is the leading cause of disability, often undiagnosed, and one of the most treatable mood disorders. As such, unobtrusively diagnosing depression is important. Many studies are starting to utilize machine learning for depression sensing from social media and Smartphone data to replace the survey instruments...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.2983035

    authors: Tlachac ML,Rundensteiner E

    更新日期:2020-11-01 00:00:00

  • 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

  • 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

  • Atrial Fibrillation Detection During Sepsis: Study on MIMIC III ICU Data.

    abstract::Sepsis is defined by life-threatening organ dysfunction during infection and is one of the leading causes of critical illness. During sepsis, there is high risk that new-onset of atrial fibrillation (AF) can occur, which is associated with significant morbidity and mortality. As a result, computer aided automated and ...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.2995139

    authors: Bashar SK,Hossain MB,Ding E,Walkey AJ,McManus DD,Chon KH

    更新日期:2020-11-01 00:00:00

  • Q-Rank: Reinforcement Learning for Recommending Algorithms to Predict Drug Sensitivity to Cancer Therapy.

    abstract::In personalized medicine, a challenging task is to identify the most effective treatment for a patient. In oncology, several computational models have been developed to predict the response of drugs to therapy. However, the performance of these models depends on multiple factors. This paper presents a new approach, ca...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.3004663

    authors: Daoud S,Mdhaffar A,Jmaiel M,Freisleben B

    更新日期:2020-11-01 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

  • A Deep Learning Based Unsupervised Method to Impute Missing Values in Patient Records for Improved Management of Cardiovascular Patients.

    abstract::Physicians increasingly depend on electronic health records (EHRs) to manage patients. However, many patient records have substantial missing values that pose a fundamental challenge to their clinical use. To address this prevailing challenge, we propose an unsupervised deep-learning method that can facilitate physici...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.3033323

    authors: Xu D,Sheng JQ,Hu PJ,Huang TS,Hsu CC

    更新日期:2020-10-23 00:00:00

  • User-Intended Doppler Measurement Type Prediction Combining CNNs With Smart Post-Processing.

    abstract::Spectral Doppler measurements are an important part of the standard echocardiographic examination. These measurements give insight into myocardial motion and blood flow providing clinicians with parameters for diagnostic decision making. Many of these measurements are performed automatically with high accuracy, increa...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.3029392

    authors: Gilbert A,Holden M,Eikvil L,Rakhmail M,Babic A,Aase SA,Samset E,McLeod K

    更新日期:2020-10-07 00:00:00

  • User independent estimations of gait events with minimal sensor data.

    abstract:GOAL:The purpose of this study was to provide an initial examination of the utility of the Beta Process - Auto Regressive - Hidden Markov Model (BP-AR-HMM) for the prior identification of gait events. A secondary objective was to determine whether the output of the model could be used for classification and prediction ...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.3028827

    authors: Donahue S,Jin L,Hahn M

    更新日期:2020-10-05 00:00:00

  • A Residual Based Attention Model for EEG Based Sleep Staging.

    abstract::Sleep staging is to score the sleep state of a subject into different sleep stages such as Wake and Rapid Eye Movement (REM). It plays an indispensable role in the diagnosis and treatment of sleep disorders. As manual sleep staging through well-trained sleep experts is time consuming, tedious, and subjective, many aut...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.2978004

    authors: Qu W,Wang Z,Hong H,Chi Z,Feng DD,Grunstein R,Gordon C

    更新日期:2020-10-01 00:00:00

  • α-Satellite: An AI-Driven System and Benchmark Datasets for Dynamic COVID-19 Risk Assessment in the United States.

    abstract::The fast evolving and deadly outbreak of coronavirus disease (COVID-19) has posed grand challenges to human society. To slow the spread of virus infections and better respond for community mitigation, by advancing capabilities of artificial intelligence (AI) and leveraging the large-scale and up-to-date data generated...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.3009314

    authors: Ye Y,Hou S,Fan Y,Zhang Y,Qian Y,Sun S,Peng Q,Ju M,Song W,Loparo K

    更新日期:2020-10-01 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

  • Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI.

    abstract::Brain Metastases (BM) complicate 20-40% of cancer cases. BM lesions can present as punctate (1 mm) foci, requiring high-precision Magnetic Resonance Imaging (MRI) in order to prevent inadequate or delayed BM treatment. However, BM lesion detection remains challenging partly due to their structural similarities to norm...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.2982103

    authors: Dikici E,Ryu JL,Demirer M,Bigelow M,White RD,Slone W,Erdal BS,Prevedello LM

    更新日期:2020-10-01 00:00:00

  • Efficient and Effective Training of COVID-19 Classification Networks With Self-Supervised Dual-Track Learning to Rank.

    abstract::Coronavirus Disease 2019 (COVID-19) has rapidly spread worldwide since first reported. Timely diagnosis of COVID-19 is crucial both for disease control and patient care. Non-contrast thoracic computed tomography (CT) has been identified as an effective tool for the diagnosis, yet the disease outbreak has placed tremen...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.3018181

    authors: Li Y,Wei D,Chen J,Cao S,Zhou H,Zhu Y,Wu J,Lan L,Sun W,Qian T,Ma K,Xu H,Zheng Y

    更新日期:2020-10-01 00:00:00

  • Deep Learning for Hemorrhagic Lesion Detection and Segmentation on Brain CT Images.

    abstract::Stroke is an acute cerebral vascular disease that is likely to cause long-term disabilities and death. Immediate emergency care with accurate diagnosis of computed tomographic (CT) images is crucial for dealing with a hemorrhagic stroke. However, due to the high variability of a stroke's location, contrast, and shape,...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.3028243

    authors: Li L,Wei M,Liu B,Atchaneeyasakul K,Zhou F,Pan Z,Kumar S,Zhang J,Pu Y,Liebeskind DS,Scalzo F

    更新日期:2020-10-01 00:00:00

  • Low-Dimensional Subject Representation-based Transfer Learning in EEG Decoding.

    abstract::Recently, the advances in passive brain-computer interfaces (BCIs) based on electroencephalogram (EEG) have shed light on real-world neuromonitoring technologies. However, human variability in the EEG activities hinders the development of practical applications of EEG-based BCI. To tackle this problem, many transfer-l...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.3025865

    authors: Jeng PY,Wei CS,Jung TP,Wang LC

    更新日期:2020-09-22 00:00:00

  • A multiprocessing scheme for PET image pre-screening, noise reduction, segmentation and lesion partitioning.

    abstract::Accurate segmentation and segmentation of lesions in PET images provide computer-aided procedures and doctors with parameters for tumour diagnosis, staging and prognosis. Currently, PET segmentation and lesion partitioning are manually measured by radiologists, which is time consuming and laborious, and tedious manual...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.3024563

    authors: Cui R,Chen Z,Wu J,Tan Y,Yu G

    更新日期:2020-09-18 00:00:00

  • Length-of-Stay Prediction for Pediatric Patients With Respiratory Diseases Using Decision Tree Methods.

    abstract::Accurate prediction of a patient's length-of-stay (LOS) in the hospital enables an efficient and effective management of hospital beds. This paper studies LOS prediction for pediatric patients with respiratory diseases using three decision tree methods: Bagging, Adaboost, and Random forest. A data set of 11,206 record...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.2973285

    authors: Ma F,Yu L,Ye L,Yao DD,Zhuang W

    更新日期:2020-09-01 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

  • Detecting Parkinsonian Tremor From IMU Data Collected in-the-Wild Using Deep Multiple-Instance Learning.

    abstract::Parkinson's Disease (PD) is a slowly evolving neurological disease that affects about [Formula: see text] of the population above 60 years old, causing symptoms that are subtle at first, but whose intensity increases as the disease progresses. Automated detection of these symptoms could offer clues as to the early ons...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2019.2961748

    authors: Papadopoulos A,Kyritsis K,Klingelhoefer L,Bostanjopoulou S,Chaudhuri KR,Delopoulos A

    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

  • 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

  • Delineation of Electrocardiograms Using Multiscale Parameter Estimation.

    abstract::The continuing interest in unobtrusive electrocardiography requires the development of algorithms, compensating for an increased number of artifacts. In previous work, we proposed a framework for robust parameter estimation of signals following a piecewise Gaussian derivative model, well suited for describing all wave...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2019.2963786

    authors: Spicher N,Kukuk M

    更新日期:2020-08-01 00:00:00

  • A Patient-Centric Health Information Exchange Framework Using Blockchain Technology.

    abstract::Health Information Exchange (HIE) exhibits remarkable benefits for patient care such as improving healthcare quality and expediting coordinated care. The Office of the National Coordinator (ONC) for Health Information Technology is seeking patient-centric HIE designs that shift data ownership from providers to patient...

    journal_title:IEEE journal of biomedical and health informatics

    pub_type: 杂志文章

    doi:10.1109/JBHI.2020.2993072

    authors: Zhuang Y,Sheets LR,Chen YW,Shae ZY,Tsai JJP,Shyu CR

    更新日期:2020-08-01 00:00:00

181 条记录 1/5 页 « 12345 »