A Comprehensive Clinical Assessment of the LumiraDx International Normalized Ratio (INR) Assay for Point-of-Care Monitoring in Anticoagulation Therapy by Riffat Munir, Elise Schapkaitz, Lara Noble, Sakina Loonat, Melanie McCree, Nazeer Ali, Barry Jacobson, Wendy Susan Stevens, Lesley Erica Scott

“…The 95% confidence intervals for the slope and intercept did not include 1.00 and 0.00, respectively; however, the total calculated error was within the minimal acceptable limits. Conclusion: The LumiraDx INR Test showed a good performance compared to laboratory-based testing and provided opportunity for rapid and patient-centric care. …”
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Mitigation of image distortion during mechanical testing within a dynamic stereo x-ray system by David N. Paglia, John M. Chomack, David V. Herlihy, Charlene Wetterstrand, Yazan Kadkoy, Roman Duchnycz, Patrick Kelly, J. Patrick O’Connor, Susan E. D’Andrea, Jason T. Maikos

“…At 103 cm, RSME was below 0.05 mm for all speeds.ConclusionWhile closer distance to the IIs and higher actuator speeds produced larger RSME, results indicated that RSME for all experimental conditions fell below the established RSME associated with DSX marker tracking. …”
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Graph-Based 3-Dimensional Spatial Gene Neighborhood Networks of Single Cells in Gels and Tissues by Zhou Fang, Kelsey Krusen, Hannah Priest, Mingshuang Wang, Sungwoong Kim, Anirudh Sriram, Ashritha Yellanki, Ankur Singh, Edwin Horwitz, Ahmet F. Coskun

“…Conclusion: 3D-spaGNN-E distinguished distinct CCCs in cell culture and tissue by examining subcellular motifs.…”
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Lessons in complexity learned during a Canadian virtual pragmatic trial for prostate cancer survivorship by Kaylen J. Pfisterer, Karen Young, Raima Lohani, Ting Xiong, Tiffane Anandarajan, Denise Ng, Tina Jiao, Caitlin Nunn, Denise Bryant-Lukosius, Ricardo Rendon, Robert J. Hamilton, Jacqueline Bender, Ian Brown, Andrew Feifer, Geoffrey Gotto, Joseph A. Cafazzo, Quynh Pham

“…Ongoing multidisciplinary stakeholder engagement was crucial for project success especially as complexities arose.Conclusion: Our approach has informed how agile adaptations can improve target implementation outcomes and may be transferable to other DHI contexts.…”
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A framework for modelling whole-lung and regional transfer factor of the lung for carbon monoxide using hyperpolarised xenon-129 lung magnetic resonance imaging by Jemima H. Pilgrim-Morris, Laurie J. Smith, Helen Marshall, Bilal A. Tahir, Guilhem J. Collier, Neil J. Stewart, Jim M. Wild

“…All models had good prediction accuracy with small mean absolute error (MAE): 1) 1.24±0.15 mmol·min−1·kPa−1, 2) 1.01±0.06 mmol·min−1·kPa−1, 3) 0.995±0.129 mmol·min−1·kPa−1. …”
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Enhancing cognitive function through blood flow restriction: An effective resistance exercise modality for middle-aged women by Dohyeon Lee, Kyeongho Byun, Sewon Lee

“…Results: Only the LLBFR condition showed significant improvements in CWST reaction time (p = 0.002) with no changes in error rates, indicating enhanced cognitive performance. …”
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Evaluation of the psychometric properties of the Copenhagen burnout inventory–student survey (CBI-SS) among health profession educational students at a university in south India by Pushpanjali Krishnappa, Medha A. Joshi, Aileen J Abraham, Avinash Prabhu, Anam Tasneem

“…The CFA fit indices included the degree of freedom, Tucker Lewis index (TLI), freedom ratio (χ²/df), Goodness-of-Fit Index (GFI), Comparative Fit Index (CFI), Root Mean Square Error Of Approximation (RMSEA), and Normed Fit Index (NFI). …”
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Addressing ORPD problem in a standard IEEE power network accompanied with RESs and FACTs appliances by COMMKE under volatile load scenarios by Susanta Dutta, Tushnik Sarkar, Chandan Paul, Sabbir Reza Tarafdar, Provas Kumar Roy, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

“…To make this comparison more lucid, statistical records are produced, box plots are presented, error bar plots are used and moreover one way ANOVA test has been performed over the results generated through the different optimization approaches.…”
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Generating synthetic brain PET images of synaptic density based on MR T1 images using deep learning by Xinyuan Zheng, Patrick Worhunsky, Qiong Liu, Xueqi Guo, Xiongchao Chen, Heng Sun, Jiazhen Zhang, Takuya Toyonaga, Adam P. Mecca, Ryan S. O’Dell, Christopher H. van Dyck, Gustavo A. Angarita, Kelly Cosgrove, Deepak D’Souza, David Matuskey, Irina Esterlis, Richard E. Carson, Rajiv Radhakrishnan, Chi Liu

“…The image translation accuracy was evaluated based on the mean squared error, structural similarity index, percentage bias and Pearson’s correlation coefficient between the ground truth and the predicted images. …”
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Plane tree risk assessment in urban space using Artificail Neural Network by Mozdeh Nafian, Mohsen Bahmani, Elham Ghehsareh Ardestani, Ali Soltani

“…Also, results of Kruskal-Wallis test showed that the risk levels of the planted trees can be significantly classified into four classes of: with no risk or healthy, low, moderate, and high-risk classes, at one percent error level. The results of Duncan's mean test showed that the number of trees in no risk and low-risk classes were significantly higher than the other classes at one percent error level. …”
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Application of <i>in vitro</i> studies to predict the pharmacokinetics of rivaroxaban tablets by A. V. Suvorova, P. A. Losenkova, Yu. V. Medvedev, E. A. Malashenko, K. K. Karnakova, N. S. Bagaeva, A. Yu. Savchenko, A. M. Poluyanov, I. E. Shohin

“…Based on the results of physiological relevance test using different schemes, pharmacokinetic profiles for a pair of drugs were predicted and the prediction error was assessed.Conclusion. A set of scientific in vitro tests was conducted for the drugs "Xarelto®, film-coated tablets, 10 mg and 20 mg", "Rivaroxaban, film-coated tablets, 10 mg and 20 mg". …”
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Application of Six Sigma management in infection control in the operating room (六西格玛管理在手术室感染控制中的应用效果) by XU Xu (徐旭), REN Guqun (任顾群), WANG Yuena (刘建荣), LIU Jianrong (高燕), GAO Yan (王小洁), WANG Xiaojie (许远乐)

“…Satisfaction rate in the observation group was higher than that in the control group(P＜0. 01). Conclusion Application of Six Sigma projects could effectively reduce the risk of operation error, iatrogenic infection and massive bleeding during and after operation, improve patient satisfaction and the management efficiency in the operating room. …”
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Healthcare workers' priorities of WHO snakebite strategic objectives for the control and prevention of snakebite envenoming in Ghana: A machine learning statistical design of exper... by Eric Nyarko, Iddrisu Abugbil Atubiga, Emmanuel Tetteh Siame, José María Gutiérrez, Eduardo Alberto Fernandez

“…To compare the performance of these models, we used several key metrics, including Akaike Information Criterion corrected (AICc), the Bayesian Information Criterion (BIC), the Root Average Squared Error (RASE), negative log-likelihood, and the total time taken to fit each model.…”
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Design and test of a double-row high-speed precision corn seed metering device with guided side-filling and posture control by Wei SU, Bo YUAN, Qinghui LAI, Shengwu ZHOU, Yuan WAN, Ruye LI

“…Bench validation tests indicated that at 12 km/h, the qualified index reached 91.45%, showing a relative error of 0.79% compared to the simulation results, thereby confirming the reliability of the simulation optimization. …”
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Scalable AI-driven air quality forecasting and classification for public health applications by Mohammad Wasil Jalali, Bahir Saidi, Habibullah Farahmand, Mohammad Aref Rezvan Panah, Eda Nur Saruhan

“…Results The TSMixer model stood out in regression tasks, achieving a high R² score of 0.9861 and a low mean squared error (MSE) of 0.0278. In classification tasks, the Random Forest model performed best with an accuracy of 99.96%, slightly outperforming XGBoost at 99.48%. …”
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The Effect of Digital Addiction Training on University Students’ Digital Addiction, Sleep Quality, and Orexin-A Levels: Randomized Controlled Trial by Zehra İncedal Sonkaya, Burak Yazgan

“…Furthermore, no significant correlation was found between orexin-A levels and both the Digital Addiction Score and the Pittsburgh Sleep Quality Index scores. Conclusion Digital addiction training has been shown to be an effective program in reducing students’ levels of overuse, non-restraint, emotional state, dependence, and overall digital addiction. …”
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Systemic lupus erythematosus and risk factors for adverse outcomes in pregnancy: a single center retrospective cohort study in Northern Brazil by Sérgio Henrique Oliveira dos Santos, Juliana Bühring, Luiz Fernando de Souza Passos, Bárbara Seabra Carneiro, Domingos Sávio Nunes de Lima, Sandra Lúcia Euzébio Ribeiro

“…Conclusion Pregnancy management in SLE presents a unique set of challenges that require a comprehensive and multidisciplinary approach. …”
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Changes in choriocapillaris blood flow density and associated factors affecting axial elongation in Chinese children and adolescents with mild to moderate myopia: a cross-sectional... by Xin Cui, Liping Chen, Hui Zheng, Xin Meng, Lu Tian, Bin Wu, Shiyong Xie, Wei Wang, Xuefeng Shi

“…A total of 288 participants aged 8 to 15 years were recruited from Tianjin Eye Hospital, including 186 children and adolescents with myopia and 102 age-matched participants without refractive error who served as the control group. Based on cycloplegic spherical equivalent (SE), the myopic participants were further categorized into moderate and mild myopia groups. …”
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A patient-reported questionnaire for evaluating utilization of the National Essential Public Health Service Program in China among older adults with hypertension and diabetes by Lu Liu, Meicen Liu, Linghe Yang, Xinyue Chen, Yuanli Liu, Lili You

“…The fit indices for the hypertension model included a Bollen–Stine bootstrap chi-square to degrees of freedom ratio (χ2/df) of 1.78, root mean square error of approximation (RMSEA) of 0.03, and goodness-of-fit index (GFI) of 0.97. …”
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Building radiomics models based on ACR TI-RADS combining clinical features for discriminating benign and malignant thyroid nodules by Xingxing Chen, Xingxing Chen, Lili Zhang, Bin Chen, Jiajia Lu

“…The calibration curve demonstrated that the mean absolute error in the training group was just 0.020 and in the test cohort was 0.033. …”
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