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  • Open Access

    ARTICLE

    Family perception of unmet support needs following a diagnosis of congenital coronary anomaly in children: Results of a survey

    Hitesh Agrawal1,2, Oriana K. Wright3, Kathleen E. Carberry1,4, S. Kristen Sexson Tejtel1,2, Carlos M. Mery1,5, Silvana Molossi1,2

    Congenital Heart Disease, Vol.12, No.6, pp. 721-725, 2017, DOI: 10.1111/chd.12473

    Abstract Background: Long-term outcome data on patients with anomalous aortic origin of coronary arteries (AAOCA) is sparse and they are often managed in a nonuniform manner. There is subjective perception of anxiety and unmet needs in these patients and families.
    Methods: An online survey of 13 questions was sent to 74 families of patients with AAOCA between May and October 2015. Descriptive statistics were performed.
    Results: A total of 31 (47%) families responded. Of these, 27 expressed the need to interact with other patients/families with AAOCA. The majority were interested in either face-to-face meetings (77%) or online support groups (71%). Regarding… More >

  • Open Access

    ARTICLE

    Myocardial bridges: Overview of diagnosis and management

    Ian S. Rogers1,2, Jennifer A. Tremmel1, Ingela Schnittger1

    Congenital Heart Disease, Vol.12, No.5, pp. 619-623, 2017, DOI:10.1111/chd.12499

    Abstract A myocardial bridge is a segment of a coronary artery that travels into the myocardium instead of the normal epicardial course. Although it is general perception that myocardial bridges are normal variants, patients with myocardial bridges can present with symptoms, such as exertional chest pain, that cannot be explained by a secondary etiology. Such patients may benefit from individualized medical/ surgical therapy. This article describes the prevalence, clinical presentation, classification, evaluation, and management of children and adults with symptomatic myocardial bridges. More >

  • Open Access

    ARTICLE

    Right aortic arch with situs solitus frequently heralds a vascular ring

    William N. Evans1,2, Ruben J. Acherman1,2, Michael L. Ciccolo1,3, Sergio A. Carrillo1,3, Gary A. Mayman1,2, Carlos F. Luna1,2, Robert C. Rollins1,2, William J. Castillo1,2, Alvaro Galindo1,2, Abraham Rothman1,2, John A. Alexander1,2, Tina W. Kwan1,2, Humberto Restrepo1,2

    Congenital Heart Disease, Vol.12, No.5, pp. 583-587, 2017, DOI:10.1111/chd.12487

    Abstract Objective: We hypothesized that a right aortic arch in situs solitus, with or without an associated cardiovascular malformation, is often associated with a vascular ring.
    Methods: From those born in Southern Nevada between March 2012 and March 2017, we identified 50 (3.6 per 10,000 live births) with a right aortic arch and situs solitus. From the 50 patients, 6 did not meet inclusion criteria for further analysis.
    Results: Of the 44 remaining, 33 (75%) had a vascular ring. Of the 33 with a vascular ring, 26 (79%) occurred with an isolated right aortic arch, and 7 (21%) had an associated… More >

  • Open Access

    ARTICLE

    Weak Fault Diagnosis of Rolling Bearing Based on Improved Stochastic Resonance

    Xiaoping Zhao1, 4, Yifei Wang2, *, Yonghong Zhang2, Jiaxin Wu1, Yunqing Shi3

    CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 571-587, 2020, DOI:10.32604/cmc.2020.06363

    Abstract Stochastic resonance can use noise to enhance weak signals, effectively reducing the effect of noise signals on feature extraction. In order to improve the early fault recognition rate of rolling bearings, and to overcome the shortcomings of lack of interaction in the selection of SR (Stochastic Resonance) method parameters and the lack of validation of the extracted features, an adaptive genetic random resonance early fault diagnosis method for rolling bearings was proposed. compared with the existing methods, the AGSR (Adaptive Genetic Stochastic Resonance) method uses genetic algorithms to optimize the system parameters, and further optimizes the parameters while considering the… More >

  • Open Access

    ARTICLE

    Prenatal detection of critical cardiac outflow tract anomalies remains suboptimal despite revised obstetrical imaging guidelines

    Heather Y. Sun1, James A. Proudfoot2, Rachel T. McCandless1

    Congenital Heart Disease, Vol.13, No.5, pp. 748-756, 2018, DOI:10.1111/chd.12648

    Abstract Background: Fetal echocardiography can accurately diagnose critical congenital heart disease prenatally, but relies on referrals from abnormalities identified on routine obstetrical ultrasounds. Critical congenital heart disease that is frequently missed due to inadequate outflow tract imaging includes anomalies such as truncus arteriosus, double outlet right ventricle, transposition of the great arteries, tetralogy of Fallot, pulmonary stenosis, and aortic stenosis.
    Objective: This study evaluated the prenatal detection rate of critical outflow tract anomalies in a single urban pediatric hospital before and after “AIUM Practice Guideline for the Performance of Obstetric Ultrasound Examinations,” which incorporated outflow tract imaging.
    Design: Infants with outflow… More >

  • Open Access

    ARTICLE

    Fetal heart size measurements as new predictors of homozygous α-thalassemia-1 in mid-pregnancy

    Xinyan Li1, Xiaoxia Qiu1, Huan Huang1, Yili Zhao2, Xueqin Li1, Meng Li1, Xiaoxian Tian1

    Congenital Heart Disease, Vol.13, No.2, pp. 282-287, 2018, DOI:10.1111/chd.12568

    Abstract Objective: To evaluate the efficacy of using fetal heart size measurements derived from axial echocardiography to predict homozygous α-thalassemia-1.
    Design: Prospective diagnostic study.
    Setting: The carrier rate of α-thalassemia-1 (–/αα) in China’s Guangxi Zhuang Autonomous Region is approximately 15%. If both parents are carriers, the risk of homozygous a-thalassemia-1 in one pregnancy is 25%.
    Patients: Singleton mid-pregnancies at risk of homozygous α-thalassemia-1 were enrolled.
    Outcome Measures: Fetal heart measurements, including heart diameter (HD), heart length (HL), heart circumference (HC), and heart area (HA), were measured. The z-scores for these heart parameters were then calculated separately based on previously constructed z-score… More >

  • Open Access

    ARTICLE

    A Performance Fault Diagnosis Method for SaaS Software Based on GBDT Algorithm

    Kun Zhu1, Shi Ying1, *, Nana Zhang1, Rui Wang1, Yutong Wu1, Gongjin Lan2, Xu Wang2

    CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1161-1185, 2020, DOI:10.32604/cmc.2020.05247

    Abstract SaaS software that provides services through cloud platform has been more widely used nowadays. However, when SaaS software is running, it will suffer from performance fault due to factors such as the software structural design or complex environments. It is a major challenge that how to diagnose software quickly and accurately when the performance fault occurs. For this challenge, we propose a novel performance fault diagnosis method for SaaS software based on GBDT (Gradient Boosting Decision Tree) algorithm. In particular, we leverage the monitoring mean to obtain the performance log and warning log when the SaaS software system runs, and… More >

  • Open Access

    ARTICLE

    Growing and Pruning Based Deep Neural Networks Modeling for Effective Parkinson’s Disease Diagnosis

    Kemal Akyol1, *

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 619-632, 2020, DOI:10.32604/cmes.2020.07632

    Abstract Parkinson’s disease is a serious disease that causes death. Recently, a new dataset has been introduced on this disease. The aim of this study is to improve the predictive performance of the model designed for Parkinson’s disease diagnosis. By and large, original DNN models were designed by using specific or random number of neurons and layers. This study analyzed the effects of parameters, i.e., neuron number and activation function on the model performance based on growing and pruning approach. In other words, this study addressed the optimum hidden layer and neuron numbers and ideal activation and optimization functions in order… More >

  • Open Access

    ARTICLE

    Comparative Study on Tree Classifiers for Application to Condition Monitoring of Wind Turbine Blade through Histogram Features Using Vibration Signals: A Data-Mining Approach

    A. Joshuva1,*, V. Sugumaran2

    Structural Durability & Health Monitoring, Vol.13, No.4, pp. 399-416, 2019, DOI:10.32604/sdhm.2019.03014

    Abstract Wind energy is considered as a alternative renewable energy source due to its low operating cost when compared with other sources. The wind turbine is an essential system used to change kinetic energy into electrical energy. Wind turbine blades, in particular, require a competitive condition inspection approach as it is a significant component of the wind turbine system that costs around 20-25 percent of the total turbine cost. The main objective of this study is to differentiate between various blade faults which affect the wind turbine blade under operating conditions using a machine learning approach through histogram features. In this… More >

  • Open Access

    ARTICLE

    Extrapolation for Aeroengine Gas Path Faults with SVM Bases on Genetic Algorithm

    Yixiong Yu*

    Sound & Vibration, Vol.53, No.5, pp. 237-243, 2019, DOI:10.32604/sv.2019.07887

    Abstract Mining aeroengine operational data and developing fault diagnosis models for aeroengines are to avoid running aeroengines under undesired conditions. Because of the complexity of working environment and faults of aeroengines, it is unavoidable that the monitored parameters vary widely and possess larger noise levels. This paper reports the extrapolation of a diagnosis model for 20 gas path faults of a double-spool turbofan civil aeroengine. By applying support vector machine (SVM) algorithm together with genetic algorithm (GA), the fault diagnosis model is obtained from the training set that was based on the deviations of the monitored parameters superimposed with the noise… More >

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