Validity and reliability of the Manchester Oxford Foot Questionnaire (MOXFQ) in one-year postoperative ankle fracture patients—a validation study by Michael Quan Nguyen, Marjolein Memelink Iversen, Knut Harboe, Ingvild Dalen, Aksel Paulsen

“…The domains had good internal consistency (McDonald’s omega 0.80 to 0.95) and test-retest reliability (ICC 0.80 to 0.92). The standard errors of measurements for the three domains were between 6.5 and 7.5, and 5.5 for the MOXFQ-Index (scale 0 to 100). …”
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Determination of the main factors of the gross regional product level by econometric modeling methods for the totality of regions of the Russian Federation by Yu. S. Ivchenko

“…Interval estimation of model parameters was carried out taking into account standard errors consistent under heteroskedasticity. The quality of models was defined by coefficient of determination, mean relative error of approximation, Ramsey’s test checking a null hypothesis about lack of the passed variables in model. …”
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Robust kinetics estimation from kinematics via direct collocation by Kuan Wang, Linlin Zhang, Leichao Liang, Jiang Shao, Xinpeng Chen, Huihao Wang

“…However, markerless motion capture can introduce varying degrees of error in tracking trajectories. This study aims to evaluate the effectiveness of the direct collocation method in estimating kinetics when joint trajectory data are impacted by noise.MethodsWe focused on walking and squatting movements as our target activities. …”
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Development of Machine Learning Prediction Models to Predict ICU Admission and the Length of Stay in ICU for COVID‑19 Patients Using a Clinical Dataset Including Chest Computed Tom... by Seyed Salman Zakariaee, Negar Naderi, Hadi Kazemi-Arpanahi

“…Results showed that with a correlation coefficient of 0.42, a mean absolute error of 2.01, and a root mean squared error of 4.11, the RF algorithm with a correlation coefficient of 0.42, mean absolute error of 2.01, and root mean squared error of 4.11demonstrated the best performance in predicting the ICU LOS of COVID-19 patients. …”
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A novel personalized homogenous finite element model to predict the pull-out strength of cancellous bone screws by Alireza Rouyin, Mohammadjavad (Matin) Einafshar, Navid Arjmand

“…When solely the cancellous bone was involved during the pull-out process (i.e., for L1, L2, and L3 vertebral bodies whose cortical bone in the inferior region is thin), the novel homogenous model yielded small mean error of < 6.0%. This error, however, increased to ~ 11% when the screw got involved to the cortical bone (for L4 and L5 vertebrae whose cortical bone in the inferior region is thick). …”
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Predicting patient visits at the psychiatric polyclinic of a public hospital in Bali, Indonesia: A forecasting approach using single exponential smoothing by Ni Made Ratih Comala Dewi Dewi, Putu Cintariasih, Ni Wayan Suryani, Luh Gde Nita Sri Wahyuningsih

“…The RMSE value was 26.8%, suggesting the average forecasting error was 26.8%. Conclusion: The single exponential smoothing method proved to be a reliable and straightforward tool for forecasting psychiatric polyclinic visits. …”
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A Methodology to Design Broadband Negative Inductors with Tight Tolerance for Microwave Applications by B. S. Buiantuev, N. S. Kalmykov, E. V. Iakovenko, D. V. Kholodnyak

“…In order to demonstrate possibilities enabled by the proposed methodology, simulation results are presented for the GHz-range negative inductors with a set of inductance and tolerance values.Conclusion. The results obtained show that the proposed methodology makes it possible to compensate the conversion error without any numerical optimization and therefore to reduce the deviation of the negative inductance from the target value in the given frequency range or to broaden the bandwidth for a given tolerable deviation of the negative inductance.…”
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Changes in Axial Length and Refractive Profile in Different Illumination: A Comparative Study to Understand the Impact of Myopia Control by Ritesh Kumar Chaurasiya, Shambhavi Vishwas, Kajal Kasana, Lokesh Chauhan, Pradeep Agarwal

“…There was a significant negative correlation between axial length and refractive error for high illumination group. Conclusion: Higher levels of illumination were associated with shorter axial length and less myopic refractive error in individuals.…”
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Design and experiment of light angle adjustable device for measuring sugar content of citrus by near infrared spectroscopy by ZENG Xianming, HAN Longbo, WEN Tao, DAI Xingyong

“…At this time, the correlation coefficient of the prediction set, the root mean square error of the prediction set, the correlation coefficient of the correction set, and the root mean square error of the correction set were 0.887 6, 0.897 5, 0.456 0, 0.430 9 °Brix, respectively. …”
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Digital Assets and the Global Economy: How the Use of Statistical Models Can Help Bitcoin Price Prediction by L. P. Bakumenko, N. S. Vasileva

“…The LSTM neural network model on a similar data set showed a MAE error equal to 2.57%.Conclusion. The analysis shows that itcoin was the most attractive investment tool during the crisis, which led to a sharp increase in its price in 2021. …”
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Minimalistic System of Characteristics of Non-linear Baseband Pulse Devices and Its Measurement by M. A. Nazarov, E. V. Semyonov

“…The transient characteristics of the filter are approximated by the model with an accuracy of no worse than 3.2 %.Conclusion. The considered system of functions can be obtained with a definable error that satisfactory for practice, which allows it to be considered as a new system of parameters for nonlinear baseband pulse devices.…”
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A Multimodal Point Cloud-Based Method for Tumor Localization in Robotic Ultrasound-Guided Radiotherapy by Lintao Song MS, Qixuan Li MS, Zhang Sai MS, Kangkang Sun MS, Wei Chen MS, Heng Zhang MS, Yibo Wang PhD, Zhuqing Jiao PhD, Xinye Ni PhD

“…The maximum error in the random positioning experiment was 1.77 mm. …”
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Method comparison and overview of refractive measurements in children: implications for myopia management by Lihua Li, Arne Ohlendorf, Siegfried Wahl, Jonas Müller, Xiaoqin Chen

“…When no cyclopentolate was used for the wavefront-based refraction (comparison 3), the bias of −0.50 D (95% limits of agreement −0.020 D to −0.97 D) was already reached at a myopic error of −2.97 D. Both astigmatic components showed no clinically relevant bias.Conclusion The spherical equivalent, measured without cycloplegic agents, led to more myopic measurements when wavefront-based refraction was used. …”
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Adjacent Joint Restriction Differentially Influences Intra- and Inter-rater Reliability and Agreement of Goniometric Measurements by Brendan L. Pinto, Tatjana Stankovic, David M. Frost, Tyson A. C. Beach

“…Intraclass correlation coefficient (ICC), standard error of measurement (SEM), along with participant, measurement/rater and random error variance were estimated…”
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Use of artificial intelligence for gestational age estimation: a systematic review and meta-analysis by Sabahat Naz, Sahir Noorani, Syed Ali Jaffar Zaidi, Abdu R. Rahman, Saima Sattar, Jai K. Das, Jai K. Das, Zahra Hoodbhoy

“…In studies using deep learning for 2D images, those employing CNN reported a mean error of 5.11 days (95% CI: 1.85, 8.37) in gestational age estimation, while one using DNN indicated a mean error of 5.39 days (95% CI: 5.10, 5.68). …”
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Validación de Sistema de Medición Antropométrica con Escáner 3d bajo las normas UNE-EN ISO20685 y NTC ISO10012 (Validation of the Anthropometric Measurement System with 3d Scanner... by Juan Fernando Arenas Betancur, Jairo Alonso Palacio Morales, César Augusto Rodríguez Ledesma

“…Los resultados arrojaron una mayor incertidumbre en la medición perimetral, una incertidumbre media en la medición cintura cuello, y la menor incertidumbre de la medición se halló en la medición del arco medial ileocrestal. En conclusión, solo este cumple con la norma al estar por debajo del máximo error permitido. …”
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Linguistic Data Model for Natural Languages and Artificial Intelligence. Part 3. Recognition by O. M. Polyakov

“…Each of these tasks has a specific dimension, the extension of tuples of parameters, blocking errors in recognition, etc. In addition, the presence of a linguistic model helps to simplify the solution of these problems. …”
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Individualized Estimation of Baseline Retinal Nerve Fiber Layer Thickness Using Conditional Variational Autoencoder by Ou Tan, PhD, Keke Liu, MD, Aiyin Chen, MD, Dongseok Choi, PhD, Jonathan C.H. Chan, MD, Bonnie N.K. Choy, MD, Kendrick C. Shih, MD, Jasper K.W. Wong, MD, Alex L.K. Ng, MD, Janice J.C. Cheung, MD, Michael Y. Ni, MD, Jimmy S.M. Lai, MD, Gabriel M. Leung, MD, Ian Y.H. Wong, MD, David Huang, MD, PhD

“…The reductions in prediction errors for NFLT profile and overall NFLT value were independently validated using the CEI data. …”
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Machine learning-based technique for directivity prediction of a compact and highly efficient 4-port MIMO antenna for 5G millimeter wave applications by Md Ashraful Haque, Kamal Hossain Nahin, Jamal Hossain Nirob, Md Kawsar Ahmed, Narinderjit Singh Sawaran Singh, Liton Chandra Paul, Abeer D. Algarni, Mohammed ElAffendi, Abdelhamied A. Ateya

“…The effectiveness of machine learning (ML) models can be estimated using a variety of different metrics, including the variance score, R square, mean square error (MSE), mean absolute error (MAE), and root mean square error (RMSE). …”
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Issues emerging in human musculoskeletal system simulation with mechanical and electromechanical rod structures by A. O. Blinov, A. V. Borisov, L. V. Konchina, M. G. Kulikova, K. S. Maslova

“…The problem of accuracy of modeling by rod robotic systems with absolutely rigid links, a link of the human musculoskeletal system, is considered. The relative error of the accuracy of approximation by rods of a human limb is calculated, a conclusion is made about a significant error in the modeling of links. …”
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