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… More >

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 >

Jinshan Lin^a*, Chunhong Dou^b, Qianqian Wang^a

Sound & Vibration, Vol.52, No.2, pp. 11-15, 2018, DOI:10.32604/sv.2018.03653

Abstract A method for gearbox fault diagnosis consists of feature extraction and fault identification. Many methods for feature extraction have been devised for exposing nature of vibration data of a defective gearbox. In addition, features extracted from gearbox vibration data are identified by various classifiers. However, existing literatures leave much to be desired in assessing performance of different combinatorial methods for gearbox fault diagnosis. To this end, this paper evaluated performance of several typical combinatorial methods for gearbox fault diagnosis by associating each of multifractal detrended fluctuation analysis (MFDFA), empirical mode decomposition (EMD) and wavelet transform More >

C. K. Madhusudana¹, N. Gangadhar¹, Hemantha Kumar, Kumar,^*,1, S. Narendranath¹

Structural Durability & Health Monitoring, Vol.12, No.2, pp. 111-127, 2018, DOI:10.3970/sdhm.2018.01262

Abstract This paper presents the fault diagnosis of face milling tool based on machine learning approach. While machining, spindle vibration signals in feed direction under healthy and faulty conditions of the milling tool are acquired. A set of discrete wavelet features is extracted from the vibration signals using discrete wavelet transform (DWT) technique. The decision tree technique is used to select significant features out of all extracted wavelet features. C-support vector classification (C-SVC) and ν-support vector classification (ν-SVC) models with different kernel functions of support vector machine (SVM) are used to study and classify the tool More >

Xiaoping Zhao¹, Jiaxin Wu^1,*, Yonghong Zhang², Yunqing Shi³, Lihua Wang²

CMC-Computers, Materials & Continua, Vol.57, No.2, pp. 223-242, 2018, DOI:10.32604/cmc.2018.02490

Abstract With the rapid development of mechanical equipment, mechanical health monitoring field has entered the era of big data. Deep learning has made a great achievement in the processing of large data of image and speech due to the powerful modeling capabilities, this also brings influence to the mechanical fault diagnosis field. Therefore, according to the characteristics of motor vibration signals (nonstationary and difficult to deal with) and mechanical ‘big data’, combined with deep learning, a motor fault diagnosis method based on stacked de-noising auto-encoder is proposed. The frequency domain signals obtained by the Fourier transform More >

Shengqun Fang¹, Zhiping Cai^1,*, Wencheng Sun¹, Anfeng Liu², Fang Liu³, Zhiyao Liang⁴, Guoyan Wang⁵

CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 419-433, 2018, DOI:10.3970/cmc.2018.02289

Abstract By using efficient and timely medical diagnostic decision making, clinicians can positively impact the quality and cost of medical care. However, the high similarity of clinical manifestations between diseases and the limitation of clinicians’ knowledge both bring much difficulty to decision making in diagnosis. Therefore, building a decision support system that can assist medical staff in diagnosing and treating diseases has lately received growing attentions in the medical domain. In this paper, we employ a multi-label classification framework to classify the Chinese electronic medical records to establish corresponding relation between the medical records and disease… More >

Hitesh Agrawal^1,2, Oriana K. Wright³, Kathleen E. Carberry^1,4, S. Kristen Sexson Tejtel^1,2, Carlos M. Mery^1,5, Silvana Molossi^1,2

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… More >

Ian S. Rogers^1,2, 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 >

William N. Evans^1,2, Ruben J. Acherman^1,2, Michael L. Ciccolo^1,3, Sergio A. Carrillo^1,3, Gary A. Mayman^1,2, Carlos F. Luna^1,2, Robert C. Rollins^1,2, William J. Castillo^1,2, Alvaro Galindo^1,2, Abraham Rothman^1,2, John A. Alexander^1,2, Tina W. Kwan^1,2, Humberto Restrepo^1,2

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 More >

Rahul Kumar Sharma^*1, V. Sugumaran¹, Hemantha Kumar², Amarnath M³

Structural Durability & Health Monitoring, Vol.11, No.1, pp. 1-16, 2017, DOI:10.3970/sdhm.2017.012.001

Abstract Most of the machineries in small or large scale industry have rotating element supported by bearings for rigid support and accurate movement. For proper functioning of machinery, condition monitoring of the bearing is very important. In present study sound signal is used to continuously monitor bearing health as sound signals of rotating machineries carry dynamic information of components. There are numerous studies in literature that are reporting superiority of vibration signal of bearing fault diagnosis. However, there are very few studies done using sound signal. The cost associated with condition monitoring using sound signal (Microphone)… More >