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Price: EUR 150.00Authors: Njezic, Sasa | Zivic, Fatima | Savic, Slobodan | Petrovic, Nenad | Pesic, Zivana Jovanovic | Stefanovic, Anja | Milenkovic, Strahinja | Grujovic, Nenad
Article Type: Research Article
Abstract: BACKGROUND: The biological properties of silicone elastomers such as polydimethylsiloxane (PDMS) have widespread use in biomedicine for soft tissue implants, contact lenses, soft robots, and many other small medical devices, due to its exceptional biocompatibility. Additive manufacturing of soft materials still has significant challenges even with major advancements that have occurred in development of these technologies for customized medical devices and tissue engineering. OBJECTIVE: The aim of this study was to develop a mathematical model of tangential stress in relation to shear stress, shear rate, 3D printing pressure and velocity, for non-Newtonian gels and fluids that …are used as materials for 3D printing. METHOD: This study used FENE (finitely extensible nonlinear elastic model) model, for non-Newtonian gels and fluids to define the dependences between tangential stress, velocity, and pressure, considering viscosity, shear stress and shear rates as governing factors in soft materials friction and adhesion. Experimental samples were fabricated as showcases, by SLA and FDM 3D printing technologies: elastic polymer samples with properties resembling elastic properties of PDMS and thermoplastic polyurethane (TPU) samples. Experimental 3D printing parameters were used in the developed analytical solution to analyse the relationships between governing influential factors (tangential stress, printing pressure, printing speed, shear rate and friction coefficient). Maple software was used for numerical modelling. RESULTS: Analytical model applied on a printed elastic polymer, at low shear rates, exhibited numerical values of tangential stress of 0.208–0.216 N m - 2 at printing velocities of 0.9 to 1.2 mm s - 1 , while the coefficient of friction was as low as 0.09–0.16. These values were in accordance with experimental data in literature. Printing pressure did not significantly influence tangential stress, whereas it was slightly influenced by shear rate changes. Friction coefficient linearly increased with tangential stress. CONCLUSION: Simple analytical model of friction for elastic polymer in SLA 3D printing showed good correspondence with experimental literature data for low shear rates, thus indicating possibility to use it for prediction of printing parameters towards desired dimensional accuracy of printed objects. Further development of this analytical model should enable other shear rate regimes, as well as additional soft materials and printing parameters. Show more
Keywords: Soft materials, tangential stress model, shear rate, friction coefficient, FENE (finitely extensible nonlinear elastic model), 3D printing
DOI: 10.3233/THC-240209
Citation: Technology and Health Care, vol. Pre-press, no. Pre-press, pp. 1-20, 2024
Authors: Lv, Guodong | Wang, Yuntao
Article Type: Review Article
Abstract: BACKGROUND: The widespread use of antibiotics has led to a gradual adaptation of bacteria to these drugs, diminishing the effectiveness of treatments. OBJECTIVE: To comprehensively assess the research progress of antibiotic resistance prediction models based on machine learning (ML) algorithms, providing the latest quantitative analysis and methodological evaluation. METHODS: Relevant literature was systematically retrieved from databases, including PubMed, Embase and the Cochrane Library, from inception up to December 2023. Studies meeting predefined criteria were selected for inclusion. The prediction model risk of bias assessment tool was employed for methodological quality assessment, and a …random-effects model was utilised for meta-analysis. RESULTS: The systematic review included a total of 22 studies with a combined sample size of 43,628; 10 studies were ultimately included in the meta-analysis. Commonly used ML algorithms included random forest, decision trees and neural networks. Frequently utilised predictive variables encompassed demographics, drug use history and underlying diseases. The overall sensitivity was 0.57 (95% CI: 0.42–0.70; p < 0.001; I 2 = 99.7%), the specificity was 0.95 (95% CI: 0.79–0.99; p < 0.001; I2 = 99.9%), the positive likelihood ratio was 10.7 (95% CI: 2.9–39.5), the negative likelihood ratio was 0.46 (95% CI: 0.34–0.61), the diagnostic odds ratio was 23 (95% CI: 7–81) and the area under the receiver operating characteristic curve was 0.78 (95% CI: 0.74–0.81; p < 0.001), indicating a good discriminative ability of ML models for antibiotic resistance. However, methodological assessment and funnel plots suggested a high risk of bias and publication bias in the included studies. CONCLUSION: This meta-analysis provides a current and comprehensive evaluation of ML models for predicting antibiotic resistance, emphasising their potential application in clinical practice. Nevertheless, stringent research design and reporting are warranted to enhance the quality and credibility of future studies. Future research should focus on methodological innovation and incorporate more high-quality studies to further advance this field. Show more
Keywords: Antibiotics, machine learning, meta-analysis, prediction
DOI: 10.3233/THC-240119
Citation: Technology and Health Care, vol. Pre-press, no. Pre-press, pp. 1-18, 2024
Authors: Begic, Zijo | Djukic, Milan | Begic, Edin | Aziri, Buena | Begic, Nedim | Badnjevic, Almir
Article Type: Research Article
Abstract: BACKGROUND: Left atrial strain (LAS) analysis represents a newer non-invasive, sensitive and specific technique for assessing left atrial (LA) function and early detection of its deformation and dysfunction. However, its applicability in mitral regurgitation (MR) in pediatric population remains unexplored, raising pertinent questions regarding its potential role in evaluating the severity and progression of the disease. OBJECTIVE: To investigate the impact of chronic MR in children and adolescents on LA remodeling and function. METHODS: The study included 100 participants. Patients with primary and secondary chronic MR lasting at least 5 years fit our …inclusion criteria. The exclusion criteria from the study were: patients with functional mitral regurgitation due to primary cardiomyopathies, patients with artificial mitral valve, patients with MR who had previously undergone surgery due to obstructive lesions of the left heart (aortic stenosis, coarctation of the aorta), patients with significant atrial rhythm disorders (atrial fibrillation, atrial flutter). The echocardiographic recordings were conducted by two different cardiologists. Outcome data was reported as mean and standard deviation (SD) or median and interquartile range (Q1–Q3). RESULTS: The study included 100 participants, of whom 50 had MR and the remaining 50 were without MR. The average age of all participants was 15.8 ± 1.2 years, with a gender distribution of 37 males and 63 females. There was a significant difference in the values of LA volume index (LAVI), which were higher in patients with MR (p = 0.0001), S/D ratio (and parameters S and D; p = 0.001, p = 0.0001, p = 0.013), mitral annulus radius (p = 0.0001), E/A ratio (p = 0.0001), as well as septal e’ (m/s), lateral e’ (m/s), and average E/e’ ratio, along with the values of TV peak gradient and LV global longitudinal strain (%). There was no significant difference in LA strain parameters, nor in LA stiffness index (LASI). CONCLUSION: Our findings revealed significant differences in several echocardiographic parameters in pediatric patients with MR relative to those without MR, providing insight into the multifaceted cardiac structural and functional effects of MR in this vulnerable population. Show more
Keywords: Left atrium, mitral regurgitation, echocardiography, fibrosis
DOI: 10.3233/THC-240768
Citation: Technology and Health Care, vol. Pre-press, no. Pre-press, pp. 1-8, 2024
Authors: Yao, Ni | Hu, Hang | Han, Chuang | Nan, Jiaofen | Li, Yanting | Zhu, Fubao
Article Type: Research Article
Abstract: BACKGROUND: The incidence of kidney tumors is progressively increasing each year. The precision of segmentation for kidney tumors is crucial for diagnosis and treatment. OBJECTIVE: To enhance accuracy and reduce manual involvement, propose a deep learning-based method for the automatic segmentation of kidneys and kidney tumors in CT images. METHODS: The proposed method comprises two parts: object detection and segmentation. We first use a model to detect the position of the kidney, then narrow the segmentation range, and finally use an attentional recurrent residual convolutional network for segmentation. RESULTS: Our …model achieved a kidney dice score of 0.951 and a tumor dice score of 0.895 on the KiTS19 dataset. Experimental results show that our model significantly improves the accuracy of kidney and kidney tumor segmentation and outperforms other advanced methods. CONCLUSION: The proposed method provides an efficient and automatic solution for accurately segmenting kidneys and renal tumors on CT images. Additionally, this study can assist radiologists in assessing patients’ conditions and making informed treatment decisions. Show more
Keywords: Computed tomography, kidney segmentation, deep learning, medical image processing
DOI: 10.3233/THC-232009
Citation: Technology and Health Care, vol. Pre-press, no. Pre-press, pp. 1-14, 2024
Authors: Harel, Daphna | Lubetzky, Anat Vilnai
Article Type: Research Article
Abstract: BACKGROUND: Standing is a basic human function that healthy adults take for granted, yet it is a complex perceptual-motor process that requires sensation of position and motion from the sensory systems. OBJECTIVE: We assessed agreement between center of pressure data from a laboratory force-platform and head position data from an HTC Vive head-mounted display (HMD) for the evaluation of standing postural control. We investigated the impact of different statistical choices when assessing the relationship between two measurements. Specifically: 1) How does correlation and agreement statistics relate before and after logarithmic transformation? 2) Is there systemic or …proportional bias between the force-platform and HMD measurements? METHODS: We tested 37 adults (26 controls, 11 with unilateral vestibular hypofunction) standing on foam, observing a static or dynamic visual scene projected from the HMD. We quantified anterior-posterior and medio-lateral sway via Directional Path, Root Mean Square Velocity, Variance, and Power Spectral Density (PSD) from a force-platform and the HMD. RESULTS: Intra-class correlations (ICCs) were moderate-to-good for the non-transformed data and good-to-excellent after logarithmic transformation for all outcomes except for PSD above 1 Hz. Correlations were higher than ICCs. Bland-Altman plots indicated proportional bias but not after logarithmic transformation. CONCLUSIONS: Both devices correlated linearly, and measure people’s postural responses but cannot be used interchangeably, mostly because they appear to diverge with larger sway as evident on Bland-Altman plots of non-transformed data. Agreement between devices was excellent for low frequency movement but poor for high frequency small corrective movements. Show more
Keywords: Virtual reality, Bland-Altman, correlations, postural control, balance
DOI: 10.3233/THC-231338
Citation: Technology and Health Care, vol. Pre-press, no. Pre-press, pp. 1-15, 2024
Authors: Chen, Han | Yang, Qiaorui | Yu, Fangjie | Shen, Yunxiang | Xia, Hong | Yang, Mengfan | Yin, Riping | Shen, Yiwei | Fan, Junfen | Fan, Zhenliang
Article Type: Research Article
Abstract: BACKGROUND: It is still unknown whether unsaturated fatty acids (UFA) have the same effect on preventing cognitive impairment in chronic kidney disease (CKD) patients as in healthy people. OBJECTIVE: To investigate the protective effect of dietary UFA intake and proportion on cognitive impairment in patients with CKD. METHODS: We extracted data from the National Health and Nutrition Examination Survey (NHANES, 2011–2014) on participants with a previous diagnosis of CKD and at least one complete cognitive assessment (Consortium to Establish a Registry for Alzheimer’s Disease test, Animal Fluency Test and Digit Symbol Substitution Test). …We used the lower quartile of the total scores of these three tests as the cut-off point, and divided the participants into two groups of normal cognitive performance and low cognitive performance to extract participants’ intake of various UFA from the NHANES dietary module. Show more
DOI: 10.3233/THC-240671
Citation: Technology and Health Care, vol. Pre-press, no. Pre-press, pp. 1-15, 2024
Authors: Chen, Pan | Wang, Xiaojie | Yan, Pijun | Jiang, Chunxia | Lei, Yi | Miao, Ying
Article Type: Research Article
Abstract: BACKGROUND: Dysfunctions in metabolism and endocrine systems are outcomes of disruptions in human physiological processes, often leading to disease onset. External factors can hinder the human body’s innate capacity for self-regulation and healing, particularly when immune responses are compromised, allowing these factors to interfere with normal bodily functions directly. OBJECTIVE: To explore the effect of uric acid expression water in blood on the occurrence of atrial fibrillation in patients with hyperthyroidism, the expression level of uric acid in the blood and other physiological indexes were compared between patients with no symptoms of atrial fibrillation and patients …with hyperthyroidism with symptoms of atrial fibrillation, to find the correlation between them. METHODS: A group of 112 hyperthyroidism patients who were admitted to our hospital from September 2019 to March 2020 were chosen and split into two groups. The control group consisted of 56 individuals (21 men and 35 women) aged between 16 and 86 years old, with an average age of 46.23 years (± 7.63). The observation group consisted of 56 individuals (24 males and 32 females) between 15 and 79 years, with an average age of 53.44 years (± 8.91). RESULTS: In the patients who were not treated with drugs before hospitalization the disease course and symptoms varied. The patients’ clinical medical and demographic data were recorded and the patients’ physiological indexes were obtained through blood tests and analysis. The differences between the two groups were analyzed by renal function, blood lipid index, thyroid function, and cardiac ultrasound, and these influencing factors were analyzed by regression analysis. The research adhered to ethical norms and ensured clear data presentation by using a rigorous technique to compare uric acid levels and physiological indicators among various patient groups. CONCLUSION: The study concentrated on the validation, repeatability, and contextual interpretation of data to provide a robust and rigorously scientific comparison. The most common is the increase of uric acid in the blood, which can induce other diseases, and atrial fibrillation is one of the most common diseases of cardiovascular diseases. Show more
Keywords: Uric acid level, serum, atrial fibrillation, hyperthyroidism, endocrine
DOI: 10.3233/THC-232028
Citation: Technology and Health Care, vol. Pre-press, no. Pre-press, pp. 1-13, 2024
Authors: Wu, Xiaoqian | Chen, Cheng | Quan, Lili
Article Type: Research Article
Abstract: BACKGROUND: Traditional methods have the limitations of low accuracy and inconvenient operation in analyzing students’ abnormal behavior. Hence, a more intuitive, flexible, and user-friendly visualization tool is needed to help better understand students’ behavior data. OBJECTIVE: In this study a visual analysis and interactive interface of students’ abnormal behavior based on a clustering algorithm were examined and designed. METHODS: Firstly, this paper discusses the development of traditional methods for analyzing students’ abnormal behavior and visualization technology and discusses its limitations. Then, the K-means clustering algorithm is selected as the solution to find potential …abnormal patterns and groups from students’ behaviors. By collecting a large number of students’ behavior data and preprocessing them to extract relevant features, a K-means clustering algorithm is applied to cluster the data and obtain the clustering results of students’ abnormal behaviors. To visually display the clustering results and help users analyze students’ abnormal behaviors, a visual analysis method and an interactive interface are designed to present the clustering results to users. The interactive functions are provided, such as screening, zooming in and out, and correlation analysis, to support users’ in-depth exploration and analysis of data. Finally, the experimental evaluation is carried out, and the effectiveness and practicability of the proposed method are verified by using big data to obtain real student behavior data. RESULTS: The experimental results show that this method can accurately detect and visualize students’ abnormal behaviors and provide intuitive analysis results. CONCLUSION: This paper makes full use of the advantages of big data to understand students’ behavior patterns more comprehensively and provides a new solution for students’ management and behavior analysis in the field of education. Future research can further expand and improve this method to adapt to more complex students’ behavior data and needs. Show more
Keywords: Clustering algorithm, student behavior, big data, visual analysis, interactive interface
DOI: 10.3233/THC-232054
Citation: Technology and Health Care, vol. Pre-press, no. Pre-press, pp. 1-17, 2024
Article Type: Research Article
Abstract: BACKGROUND: Double rocking jump rope training can effectively enhance physical recovery, adaptability to exercise load, and lower limb muscle strength of badminton players in sports colleges, thus offering valuable insights for improving training methods in sports colleges and universities. OBJECTIVE: To investigate the effect of double rocking jump rope training on the lower limb muscle strength of badminton players specializing in badminton in sports colleges. METHODS: An experimental study was conducted through a ten-week teaching intervention experiment with badminton players. Relevant heart rate indexes and badminton related lower limb muscle strength indexes were …measured before and after the experiment. The data of the measured relevant indexes were statistically and analytically analyzed. At the end of the experiment, the physical recovery level and the heart’s adaptability to the exercise load of the control group were improved, and the lower limb muscle strength test indexes and sports performance were better than before the experiment. In the experimental group, badminton players’ physical function, anaerobic metabolism of the body and other aspects also improved. RESULTS: The physical function of the experimental group of badminton players, the energy supply capacity of the body anaerobic metabolism and aerobic work capacity all have an enhancement effect, enabling badminton players to adapt to large exercise loads quickly and improve the recovery rate of physical fitness. CONCLUSION: The introduction of double rocking jump rope into badminton training classes in sports colleges and universities as a means of lower limb muscle strength training is conducive to improving the level of lower limb muscle strength of special badminton players, enriching the teaching and training means of lower limb muscle strength in sports colleges and universities, and broadening the research field of lower limb muscle strength in badminton in sports colleges and universities. Show more
Keywords: Double rocking jump rope, badminton, lower limb muscle strength, AdaBoost algorithm optimization
DOI: 10.3233/THC-231868
Citation: Technology and Health Care, vol. Pre-press, no. Pre-press, pp. 1-18, 2024
Authors: Lu, Jian-Lin | Yuan, Xiao-Yan | Zhang, Jin-Shan | Li, Yuan
Article Type: Research Article
Abstract: BACKGROUND: Ever since the GALAD (gender-age-Lens culinaris agglutinin-reactive alpha-fetoprotein-alpha-fetoprotein-des-gamma-carboxy prothrombin) logistic regression model was established to diagnose hepatocellular carcinoma (HCC), there has been no high-level evidence that evaluates and summarizes it. OBJECTIVE: This meta-analysis was performed to assess the diagnostic ability of the GALAD model. METHODS: The following databases were systematically searched for original diagnostic studies on HCC: PubMed, Embase, Medline, the Web of Science, Cochrane Library, China National Knowledge Infrastructure Wanfang (China), Wiper and the Chinese BioMedical Literature Database. After screening the search results according to our criteria, the Quality Assessment …of Diagnostic Accuracy Studies 2 tool was used to evaluate the methodologic qualities, and statistical software were used to output the statistics. RESULTS: Ultimately, 10 studies were included and analyzed. The results revealed the pooled sensitivity and specificity of the GALAD model to be 0.86 (95% confidence interval [CI]: 0.82, 0.90) and 0.90 (95% CI: 0.87, 0.92), respectively, for all-stage HCC. The area under the curve (AUC) was 0.94. For early-stage HCC, the pooled sensitivity and specificity of the GALAD model were 0.83 (95% CI: 0.78, 0.87) and 0.81 (95% CI: 0.78, 0.83), respectively. The AUC was 0.90. CONCLUSION: This meta-analysis confirmed that the GALAD model has excellent diagnostic performance for early-stage and all-stage HCC and can maintain high sensitivity and specificity in early-stage HCC. Therefore, the GALAD model is qualified for screening early-stage canceration from chronic liver disease. Show more
Keywords: HCC, logistic models, biomarkers, diagnostic efficiency, early detection of cancer
DOI: 10.3233/THC-231470
Citation: Technology and Health Care, vol. Pre-press, no. Pre-press, pp. 1-15, 2024
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