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Alice van Zon, Yvette E Smulders, Inge Stegeman, Geerte G J Ramakers, Veronique J C Kraaijenga, Simone P C Koenraads, Gijsbert A Van Zanten, Albert B Rinia, Robert J Stokroos, Rolien H Free, Johan H M Frijns, Wendy J Huinck, Emmanuel A M Mylanus, Rinze A Tange, Adriana L Smit, Hans G X M Thomeer, Vedat Topsakal, Wilko Grolman
OBJECTIVES/HYPOTHESIS: To investigate hearing capabilities and self-reported benefits of simultaneous bilateral cochlear implantation (BiCI) compared with unilateral cochlear implantation (UCI) after a 2-year follow-up and to evaluate the learning effect of cochlear implantees over time. STUDY DESIGN: Multicenter randomized controlled trial. METHODS: Thirty-eight postlingually deafened adults were included in this study and randomly allocated to either UCI or simultaneous BiCI...
September 26, 2016: Laryngoscope
Nivethitha Somu, M R Gauthama Raman, Kannan Kirthivasan, V S Shankar Sriram
The impact of internet and information systems across various domains have resulted in substantial generation of multidimensional datasets. The use of data mining and knowledge discovery techniques to extract the original information contained in the multidimensional datasets play a significant role in the exploitation of complete benefit provided by them. The presence of large number of features in the high dimensional datasets incurs high computational cost in terms of computing power and time. Hence, feature selection technique has been commonly used to build robust machine learning models to select a subset of relevant features which projects the maximal information content of the original dataset...
November 2016: Journal of Medical Systems
Thrissia Koralek, Miryha G Runnerstrom, Brandon J Brown, Chukwuemeka Uchegbu, Tania B Basta
Objectives. We examined the role of outbreak information sources through four domains: knowledge, attitudes, beliefs, and stigma related to the 2014 Ebola virus disease (EVD) outbreak. Methods. We conducted an online survey of 797 undergraduates at the University of California, Irvine (UCI) and Ohio University (OU) during the peak of the outbreak. We calculated individual scores for domains and analyzed associations to demographic variables and news sources. Results. Knowledge of EVD was low and misinformation was prevalent...
2016: PLoS Currents
L Di Luzio, E Masi, L Mandia, C Castagna, M Meroni, E Ferrazzi
No abstract text is available yet for this article.
September 2016: Ultrasound in Obstetrics & Gynecology
Oscar E Pecho, María M Pérez, Razvan Ghinea, Alvaro Della Bona
OBJECTIVES: To analyze the influence of lightness, chroma and hue differences on visual shade matching performed by dental students. METHODS: 100 dental students (DS) volunteers with normal vision participated in the study. A spectroradiometer (SP) was used to measure the spectral reflectance of 4 extracted human upper central incisors (UCI 1-4) and shade tabs from Vita Classical (VC) and Vita Toothguide 3D-Master (3D) shade guides. Measurements were performed over a gray background, inside a viewing booth and under D65 illuminant (diffuse/0° geometry)...
September 7, 2016: Dental Materials: Official Publication of the Academy of Dental Materials
Muhammad Sadiq Khan, Mohammed Ali Al-Garadi, Ainuddin Wahid Abdul Wahab, Tutut Herawan
Soft set theory is a mathematical approach that provides solution for dealing with uncertain data. As a standard soft set, it can be represented as a Boolean-valued information system, and hence it has been used in hundreds of useful applications. Meanwhile, these applications become worthless if the Boolean information system contains missing data due to error, security or mishandling. Few researches exist that focused on handling partially incomplete soft set and none of them has high accuracy rate in prediction performance of handling missing data...
2016: SpringerPlus
Anna J Warren, Danny Axford, Neil G Paterson, Robin L Owen
A reproducible, and sample independent means of predictably obtaining large, well-ordered crystals has proven elusive in macromolecular crystallography. In the structure determination pipeline, crystallisation often proves to be a rate-limiting step, and the process of obtaining even small or badly ordered crystals can prove time-consuming and laborious. This is particularly true in the field of membrane protein crystallography and this is reflected in the limited number of unique membrane protein structures deposited in the protein data bank (less than 650 by June 2016 - http://blanco...
2016: Advances in Experimental Medicine and Biology
Siti Norul Huda Sheikh Abdullah, Farah Aqilah Bohani, Baher H Nayef, Shahnorbanun Sahran, Omar Al Akash, Rizuana Iqbal Hussain, Fuad Ismail
Brain magnetic resonance imaging (MRI) classification into normal and abnormal is a critical and challenging task. Owing to that, several medical imaging classification techniques have been devised in which Learning Vector Quantization (LVQ) is amongst the potential. The main goal of this paper is to enhance the performance of LVQ technique in order to gain higher accuracy detection for brain tumor in MRIs. The classical way of selecting the winner code vector in LVQ is to measure the distance between the input vector and the codebook vectors using Euclidean distance function...
2016: Computational and Mathematical Methods in Medicine
Z Zhang, S Ravassa, W Y Yang, T Petit, Z Petra, B Lopez, F F Wei, C Pontillo, L Thijs, L Jacobs, A Gonzalez, T Koeck, D Christian, J U Voigt, P Verhamme, T Kuznetsova, J Diez, H Mischak, J A Staessen
OBJECTIVE: Moving from multidimensional urinary proteomic markers to single urinary collagen fragments and linking these fragments to serum biomarkers of myocardial collagen turnover may generate new insights in the pathophysiology of diastolic LV function. DESIGN AND METHOD: In 782 randomly recruited Flemish (51.3% women; 50.5 years), we assessed diastolic LV function by echocardiography, sequenced urinary collagen I (uCI) and III (uCIII) fragments, and determined serum markers of collagen I synthesis (PICP, carboxyterminal propeptide of procollagen) and breakdown (CITP, carboxyterminal telopeptide) and the tissue inhibitor of matrix metalloproteinase type 1 (TIMP 1)...
September 2016: Journal of Hypertension
Levente Kovács, Fruzsina Luca Kézér, Ferenc Ruff, Ottó Szenci
Peripartal autonomic nervous system function and early maternal behavior were investigated in 79 multiparous Holstein-Friesian cows. Animals were allocated into four groups based on the technology of calving management: 1) unassisted calving in a group pen (UCG; N=19), 2) unassisted calving in an individual pen (UCI; N=21), 3) assisted calving with appropriately timed obstetrical assistance (ACA; N=20), and 4) assisted calving with premature obstetrical assistance (ACP; N=19). Heart rate, the high frequency (HF) component of heart rate variability (HRV) as a measure of vagal activity and the ratio between the low frequency (LF) and HF components (LF/HF ratio) as a parameter of sympathetic nervous system activity were calculated...
October 15, 2016: Physiology & Behavior
Bent R Rønnestad, Joar Hansen, Geir Vegge, Iñigo Mujika
Endurance athletes usually achieve performance peaks with 2-4 weeks of overload training followed by 1-3weeks of tapering. With a tight competition schedule, this may not be appropriate. This case investigates the effect of a 7-day overload period including daily high-intensity aerobic training followed by a 5-day step taper between two competitions in an elite cross-country mountain biker. Pre-test peak oxygen consumption was 89 ml·kg(-1)·min(-1), peak aerobic power 6.8 W·kg(-1), power output at 2 mmol·L(-1) blood lactate concentration 3...
August 1, 2016: Journal of Sports Sciences
Yi Wang, Yi Li, Weilin Pu, Kathryn Wen, Yin Yao Shugart, Momiao Xiong, Li Jin
Efficiency, memory consumption, and robustness are common problems with many popular methods for data analysis. As a solution, we present Random Bits Forest (RBF), a classification and regression algorithm that integrates neural networks (for depth), boosting (for width), and random forests (for prediction accuracy). Through a gradient boosting scheme, it first generates and selects ~10,000 small, 3-layer random neural networks. These networks are then fed into a modified random forest algorithm to obtain predictions...
2016: Scientific Reports
L Kovács, F L Kézér, O Szenci
Welfare aspects of obstetrical assistance were studied in multiparous Holstein-Friesian cows (n=176) with (1) unassisted calving in an individual pen (UCIP; n=42), (2) unassisted calving in a group pen (UCG; n=48), (3) assisted calving with appropriately timed obstetrical assistance (ACAP; n=50), and (4) assisted calving with inappropriately timed (premature) obstetrical assistance (ACIN; n=36). Duration of the stages of calving, the prevalence and the degree of dystocia, stillbirth ratio, newborn calf vitality, and the occurrence of postpartum health problems (i...
September 2016: Journal of Dairy Science
Ricardo Santana Veiga, João Cassis, Pedro Oliveira, António Lopez-Beltran
BACKGROUND: Inverted papilloma (IP) is an unusual benign neoplasm, most commonly found in the bladder. Cases of malignant transformation have been reported in the past, although most of them are now considered to be urothelial carcinomas with an inverted growth pattern. CASE: A 54-year-old man was diagnosed with urothelial carcinoma in situ (UCIS), high-grade papillary urothelial carcinoma (HGPUC), and IP by transurethral resection specimen of the bladder. The urothelial carcinoma cells were seen colonizing the inverted papilloma...
February 2016: Analytical and Quantitative Cytopathology and Histopathology
Zewei Chen, Xin Zhang, Zhuoyong Zhang
PURPOSE: Timely risk assessment of chronic kidney disease (CKD) and proper community-based CKD monitoring are important to prevent patients with potential risk from further kidney injuries. As many symptoms are associated with the progressive development of CKD, evaluating risk of CKD through a set of clinical data of symptoms coupled with multivariate models can be considered as an available method for prevention of CKD and would be useful for community-based CKD monitoring. METHODS: Three common used multivariate models, i...
June 22, 2016: International Urology and Nephrology
Forest Agostinelli, Nicholas Ceglia, Babak Shahbaba, Paolo Sassone-Corsi, Pierre Baldi
MOTIVATION: Circadian rhythms date back to the origins of life, are found in virtually every species and every cell, and play fundamental roles in functions ranging from metabolism to cognition. Modern high-throughput technologies allow the measurement of concentrations of transcripts, metabolites and other species along the circadian cycle creating novel computational challenges and opportunities, including the problems of inferring whether a given species oscillate in circadian fashion or not, and inferring the time at which a set of measurements was taken...
June 15, 2016: Bioinformatics
Derya Avci, Akif Dogantekin
Parkinson disease is a major public health problem all around the world. This paper proposes an expert disease diagnosis system for Parkinson disease based on genetic algorithm- (GA-) wavelet kernel- (WK-) Extreme Learning Machines (ELM). The classifier used in this paper is single layer neural network (SLNN) and it is trained by the ELM learning method. The Parkinson disease datasets are obtained from the UCI machine learning database. In wavelet kernel-Extreme Learning Machine (WK-ELM) structure, there are three adjustable parameters of wavelet kernel...
2016: Parkinson's Disease
Mahnaz Behroozi, Ashkan Sami
Recently, speech pattern analysis applications in building predictive telediagnosis and telemonitoring models for diagnosing Parkinson's disease (PD) have attracted many researchers. For this purpose, several datasets of voice samples exist; the UCI dataset named "Parkinson Speech Dataset with Multiple Types of Sound Recordings" has a variety of vocal tests, which include sustained vowels, words, numbers, and short sentences compiled from a set of speaking exercises for healthy and people with Parkinson's disease (PWP)...
2016: International Journal of Telemedicine and Applications
Li-Yu Hu, Ya-Han Hu, Chih-Fong Tsai, Jian-Shian Wang, Min-Wei Huang
Classification is one of the most important technologies used in data mining. Researchers have recently proposed several classification techniques based on the concept of association rules (also known as CBA-based methods). Experimental evaluations on these studies show that in average the CBA-based approaches can yield higher accuracy than some of conventional classification methods. However, conventional CBA-based methods adopt a single threshold of minimum support for all items, resulting in the rare item problem...
2016: SpringerPlus
Meng-Fong Tsai, Shyr-Shen Yu
An imbalanced classification means that a dataset has an unequal class distribution among its population. For any given dataset, regardless of any balancing issue, the predictions made by most classification methods are highly accurate for the majority class but significantly less accurate for the minority class. To overcome this problem, this study took several imbalanced datasets from the famed UCI datasets and designed and implemented an efficient algorithm which couples Top-N Reverse k-Nearest Neighbor (TRkNN) with the Synthetic Minority Oversampling TEchnique (SMOTE)...
July 2016: Journal of Medical Systems
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