Cardiovascular diseases (CVD) are one of the major global health threats, causing millions of deaths each year. According to data from the World Health Organization, over 500 million people are affected by cardiovascu...
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Eye-tracking studies focused on art galleries and museums within the realm of Instagram, especially in the Indonesian context, are notably scant. This investigation elucidates the user interaction and experience of th...
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Age-related hearing loss (ARHL) is primarily attributed to inner-ear factors, yet the role of age-related middle ear characteristics remains elusive. Employing a finite element (FE) model, we conducted a comparative a...
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Respiratory rate (RR) monitoring is crucial in clinical and healthcare settings. With advancements in microelectromechanical system (MEMS) technology, monitoring respiration using seismocardiogram (SCG) has emerged as...
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Background and objectives: Hearing loss is a crucial global health hazard exerting considerable social and physiological effects on spoken language and cognition. Patients affected by this condition may experience soc...
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Background and objectives: Hearing loss is a crucial global health hazard exerting considerable social and physiological effects on spoken language and cognition. Patients affected by this condition may experience social and professional hardships that dominate occupational injuries. Therefore, the identification of the features of recessive hearing loss is important for clinicians to prevent further disease progression. This work aimed to develop a hybrid statistical and machine-learning approach as a decision-support mechanism. We expect the proposed model to help predict hearing-loss disorders and support clinical diagnosis. Methods: A three-phase hybrid approach was proposed to implement classification models. A stepwise method and a random forest (RF) technique were utilized as filters during feature selection. Phase I involved reducing the number of input variables and selecting the most influential features. Phase II included the use of an oversampling technique called synthetic minority oversampling technique (SMOTE) to oversample the minority class and balance the sample size between the target and nontarget classes. Phase III focused on the final model selection based on three supervised classification models, namely, the logistic regression, multilayer perceptron, and support vector machine (SVM), for the target identification and prediction of the case of interest (i.e., hearing loss). Results: The analysis of phase I involved the selection and acquisition of three and seven features through the stepwise technique and RF method, respectively. The SMOTE technique alleviated the imbalanced data issue and improved the predictive capability substantially in phase II and III. Accordingly, in terms of accuracy, precision, recall, and F1 score, our empirical results demonstrated that the proposed hybrid approach involving the SVM method combined with a stepwise technique was competitive against the logistic model featuring all variables. Furthermore, the SVM mo
Stroke is one of cerebrovascular diseases caused by the obstruction of blood flow to the brain. Stroke becomes the leading cause of death in Indonesia and the second in the world. Stroke also causes of the disability....
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The objective of this study was to compare and correlate the Portable Ultra Sound (US) measuring technique to the skinfold measuring technique (SF) to estimate body fat percentage (%F) in young adults. Sixty military ...
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ISBN:
(纸本)9781457717871
The objective of this study was to compare and correlate the Portable Ultra Sound (US) measuring technique to the skinfold measuring technique (SF) to estimate body fat percentage (%F) in young adults. Sixty military were evaluated, all males, divided in two groups: Group 1 (normal) composed by 30 military with Body Mass Index (BMI) until 24.99 kg/m(2) and Group 2 (overweight) composed by 30 military with BMI > 25 kg/m(2). Weight, height, skinfolds and ultrasound were measured in 9 points (triceps, subscapular, biceps, chest, medium axillary, abdominal, suprailiac, thigh and calf). Body fat average values obtained by skinfold thickness and ultrasound measurements were 13.25 +/- 6.32 % and 12.73 +/- 5.95 % respectively. Despite significant differences in measurements of each anatomical site, it was possible to verify that the total final body fat percentage calculated by both techniques did not present significant differences and that overweight group presented greater similarity between the values obtained using caliper and ultrasound equipment.
Cigarette smoking is reported to be the major risk factor for endothelial dysfunction. The variations of the spectral compositions of microcirculatory perfusion signal could provide the information related to the regu...
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Nanocomposite (NC) hydrogels used for sonodynamic therapy (SDT) face challenges such as lacking interfacial interactions between the polymers and nanomaterials as well as presenting uneven dispersion of nanomaterials ...
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Spinocerebellar ataxia is a neurological disorder characterized by impaired neural coordination, leading to unstable gait, coordination difficulties, and other motor abnormalities. This disease significantly impacts p...
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