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 tremendous pressure on radiologists for reading the exams and may potentially lead to fatigue-related mis-diagnosis. Reliable automatic classification algorithms can be really helpful; however, they usually require a considerable number of COVID-19 cases for training, which is difficult to acquire in a timely manner. Meanwhile, how to effectively utilize the existing archive of non-COVID-19 data (the negative samples) in the presence of severe class imbalance is another challenge. In addition, the sudden disease outbreak necessitates fast algorithm development. In this work, we propose a novel approach for effective and efficient training of COVID-19 classification networks using a small number of COVID-19 CT exams and an archive of negative samples. Concretely, a novel self-supervised learning method is proposed to extract features from the COVID-19 and negative samples. Then, two kinds of soft-labels ('difficulty' and 'diversity') are generated for the negative samples by computing the earth mover's distances between the features of the negative and COVID-19 samples, from which data 'values' of the negative samples can be assessed. A pre-set number of negative samples are selected accordingly and fed to the neural network for training. Experimental results show that our approach can achieve superior performance using about half of the negative samples, substantially reducing model training time.
journal_name
IEEE J Biomed Health Informjournal_title
IEEE journal of biomedical and health informaticsauthors
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 Ydoi
10.1109/JBHI.2020.3018181subject
Has Abstractpub_date
2020-10-01 00:00:00pages
2787-2797issue
10eissn
2168-2194issn
2168-2208journal_volume
24pub_type
杂志文章abstract:OBJECTIVE:This paper presents a methodology to automatically screen for sleep apnea based on the detection of apnea and hypopnea events in the blood oxygen saturation (SpO2) signal. METHODS:It starts by detecting all desaturations in the SpO2 signal. From these desaturations, a total of 143 time-domain features are ex...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2018.2817368
更新日期:2019-03-01 00:00:00
abstract::The computer-aided diagnosis for histopathological images has attracted considerable attention. Principal component analysis network (PCANet) is a novel deep learning algorithm for feature learning with the simple network architecture and parameters. In this study, a color pattern random binary hashing-based PCANet (C...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2016.2602823
更新日期:2017-09-01 00:00:00
abstract::Mental illness has a deep impact on individuals, families, and by extension, society as a whole. Social networks allow individuals with mental disorders to communicate with others sufferers via online communities, providing an invaluable resource for studies on textual signs of psychological health problems. Mental di...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2016.2543741
更新日期:2016-07-01 00:00:00
abstract::Automated tissue classification is an essential step for quantitative analysis and treatment of emphysema. Although many studies have been conducted in this area, there still remain two major challenges. First, different emphysematous tissue appears in different scales, which we call "inter-class variations." Second, ...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2018.2890045
更新日期:2019-11-01 00:00:00
abstract::In the analysis of histopathological images, both holistic (e.g., architecture features) and local appearance features demonstrate excellent performance, while their accuracy may vary dramatically when providing different inputs. This motivates us to investigate how to fuse results from these features to enhance the a...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2015.2461671
更新日期:2016-09-01 00:00:00
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
更新日期:2020-11-01 00:00:00
abstract::Multichannel image registration is an important challenge in medical image analysis. Multichannel images result from modalities such as dual-energy CT or multispectral microscopy. Besides, multichannel feature images can be derived from acquired images, for instance, by applying multiscale feature banks to the origina...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2018.2844361
更新日期:2019-05-01 00:00:00
abstract:OBJECTIVE:to provide a proof-of-concept tool for segmenting chronic wounds and transmitting the results as instructions and coordinates to a bioprinter robot and thus facilitate the treatment of chronic wounds. METHODS:several segmentation methods used for measuring wound geometry, including edge-detection and morphol...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2017.2743526
更新日期:2018-07-01 00:00:00
abstract::This paper presents a novel three-stage blood vessel segmentation algorithm using fundus photographs. In the first stage, the green plane of a fundus image is preprocessed to extract a binary image after high-pass filtering, and another binary image from the morphologically reconstructed enhanced image for the vessel ...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2014.2335617
更新日期:2015-05-01 00:00:00
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
更新日期:2020-09-22 00:00:00
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
更新日期:2020-12-01 00:00:00
abstract::Intelligently extracting knowledge from social media has recently attracted great interest from the Biomedical and Health Informatics community to simultaneously improve healthcare outcomes and reduce costs using consumer-generated opinion. We propose a two-step analysis framework that focuses on positive and negative...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2014.2336251
更新日期:2015-01-01 00:00:00
abstract::Robotic-assisted needle steering can enhance the accuracy of needle-based interventions. Application of current needle steering techniques are restricted by the limited deflection curvature of needles. Here, a novel steerable needle with improved curvature is developed and used with an online motion planner to steer t...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2017.2780192
更新日期:2018-11-01 00:00:00
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
更新日期:2020-12-01 00:00:00
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
更新日期:2020-10-05 00:00:00
abstract::The role of sensing technologies, such as wearables, in delivering precision care is becoming widely acceptable. Given the very large quantities of sensor data that rapidly accumulate, there is a need to employ automated algorithms to label biosignal sensor data. In many real-life clinical applications, no such expert...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2018.2820054
更新日期:2019-01-01 00:00:00
abstract::The classification of six types of white blood cells (WBCs) is considered essential for leukemia diagnosis, while the classification is labor-intensive and strict with the clinical experience. To relieve the complicated process with an efficient and automatic method, we propose the Attention-aware Residual Network bas...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2020.3012711
更新日期:2020-07-29 00:00:00
abstract:BACKGROUND AND OBJECTIVE:New technology enables constant boost to the powers of mobile devices, which in the previous years have transformed from simple mobile phones to smart phones. Computational powers of these electronics enable actions that previously were possible only for computers. By the use of special applica...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2019.2891729
更新日期:2019-09-01 00:00:00
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
更新日期:2020-09-01 00:00:00
abstract::To achieve effective and efficient detection of Alzheimer's disease (AD), many machine learning methods have been introduced into this realm. However, the general case of limited training samples, as well as different feature representations typically makes this problem challenging. In this paper, we propose a novel m...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2013.2285378
更新日期:2014-05-01 00:00:00
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
更新日期:2014-01-01 00:00:00
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
更新日期:2016-05-01 00:00:00
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
更新日期:2020-10-27 00:00:00
abstract::We present in this paper novel techniques that determine the semantic relationships among GeneOntology (GO) terms. We implemented these techniques in a prototype system called GoSE, which resides between user application and GO database. Given a set S of GO terms, GoSE would return another set S' of GO terms, where ea...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/jbhi.2013.2248742
更新日期:2013-05-01 00:00:00
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
更新日期:2020-09-18 00:00:00
abstract::Gait impairment in multiple sclerosis (MS) can result from muscle weakness, physical fatigue, lack of coordination, and other symptoms. Walking speed, as measured by a number of clinician-administered walking tests, is the primary measure of gait impairment used by clinical researchers, but inertial gait features from...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2017.2773629
更新日期:2018-01-01 00:00:00
abstract::Ultrasound imaging has become a prevalent examination method in prenatal diagnosis. Accurate acquisition of fetal facial standard plane (FFSP) is the most important precondition for subsequent diagnosis and measurement. In the past few years, considerable effort has been devoted to FFSP recognition using various hand-...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2017.2705031
更新日期:2018-05-01 00:00:00
abstract::Blood biochemistry attributes form an important class of tests, routinely collected several times per year for many patients with diabetes. The objective of this study is to investigate the role of blood biochemistry for improving the predictive accuracy of the diagnosis of cardiac autonomic neuropathy (CAN) progressi...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/JBHI.2014.2363177
更新日期:2016-01-01 00:00:00
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
更新日期:2020-11-01 00:00:00
abstract::The development of a system for the automatic, objective, and reliable detection of cough events is a need underlined by the medical literature for years. The benefit of such a tool is clear as it would allow the assessment of pathology severity in chronic cough diseases. Even though some approaches have recently repo...
journal_title:IEEE journal of biomedical and health informatics
pub_type: 杂志文章
doi:10.1109/jbhi.2013.2239303
更新日期:2013-05-01 00:00:00