Comparing the Effect of Monofocal and Multifocal Intraocular Lenses on Macular Surgery by A. Altun

“…The effects of refraction error and IOL decentration at the time of macular surgery performed for ERM and ILM peeling, according to the lens type, were investigated. …”
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Development of a Method of Analysis of Ofloxacin in the Complex Preparation "Ofloxazol" by T. A. Kobeleva, A. I. Sichko, A. I. Zamaraeva, N. S. Bessonova

“…Statistical processing of the analysis results showed that the relative error of quantitative determination does not exceed ±1.66 %. …”
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Design of a Demodulation Algorithm for UWOC based on Improved Manchester Coding by ZHANG You, HU Fangren, ZHAO Xiaoyan, ZHOU Jun, WANG Qilong

“…Finally, high-speed communication system with low BER is realized by using Manchester encoding sub-frame headers and Reed-Solomon (RS) error-correcting codes in the data part. The algorithm is designed and implemented on a Field Programmable Gate Array (FPGA), and a UWOC system using this method is built to conduct BER tests under different environments and distances.…”
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Time-Series analysis of short-term exposure to air pollutants and daily hospital admissions for stroke in Tabriz, Iran. by Shahryar Razzaghi, Saeid Mousavi, Mehran Jaberinezhad, Ali Farshbaf Khalili, Seyed Mahdi Banan Khojasteh

“…The goodness of fit measures, Root Mean Squared Error (RMSE), and Median Absolute Error (MAE) were 1.81 and 1.19, respectively.…”
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Techniques for Accelerometer Reading Processing on Railway Transport Using Wavelet Transform by A. M. Boronakhin, A. V. Bolshakova, D.  M. Klionskiy, D. Yu. Larionov, R. V. Shalymov

“…The results show that the discrete wavelet transform is effective for multiresolution and multiband analysis, and continuous wavelet transform and wavelet scalogram allows extraction of irregularities and determination of their parameters. The relative error for irregularity depth was improved by 18 %, and the absolute error for irregularity length determinations was reduced by 7 times.Conclusion. …”
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Methods to quantify soft tissue-based cranial growth and treatment outcomes in children: a systematic review. by Sander Brons, Machteld E van Beusichem, Ewald M Bronkhorst, Jos M Draaisma, Stefaan J Bergé, Jan G Schols, Anne Marie Kuijpers-Jagtman

“…In general, the measurement error was below 2 mm, and correlation coefficients were very good.…”
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An interpretable and stacking ensemble model for predicting heat and mass transfer of desiccant wheel by Mengyang Li, Liu Chen

“…Coefficient of Determination (R2), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE) were used to measure this stacking model: the process side outlet temperature (R2 = 0.9467, RMSE=1.5239, and MAE = 1.2721), the process side outlet humidity ratio (R2 = 0.9743, RMSE = 0.5728, MAE = 0.4531). …”
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Evaluation and Refractive Results Comparison of MIOL-­SOFT-­2­-13 IOL Implantation with Foreign Models by D. F. Belov, V. P. Nikolaenko, V. V. Kovaleva

“…A month after PE spherical equivalent of refraction was assessed by Topcon­8800 (Japan). Mean calculation error (ME) and mean absolute error (MAE) were used as a IOL calculation accuracy criterion. …”
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Estimating spatiotemporal patterns of deaths by COVID-19 outbreak on a global scale by Fernanda Valente, Marcio Poletti Laurini

“…To bypass the aforementioned problems, we propose a method to estimate the components of trend, seasonality and cycle in COVID-19 data, controlling for the presence of measurement error and considering the spatial heterogeneity. …”
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Pulse2AI: An Adaptive Framework to Standardize and Process Pulsatile Wearable Sensor Data for Clinical Applications by Sicong Huang, Roozbeh Jafari, Bobak J. Mortazavi

“…For respiration rate (RR) estimation, Pulse2AI boosted performance by 19.69&#x0025;, from 1.47 to 1.18 breaths per minute (BrPM) in mean-absolute-error (MAE). <italic>Conclusion:</italic> Pulse2AI turns pulsatile signals into machine learning (ML) ready datasets for arbitrary remote health monitoring tasks. …”
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DIAGNOSIS AND PREDICTION OF CHOLECYSTITIS DEVELOPMENT ON THE BASIS OF NEURAL NETWORK ANALYSIS OF RISK FACTORS by V. A. Lazarenko, A. E. Antonov

“…The difference between the mean calculated and mean empirical values was 0.45 for the training set and 1.75 for the clinical approbation group. The mean absolute error was within the range of 1.87–2.07 years.Conclusion. 1. …”
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Predictive model to identify multiple synergistic effects of geriatric syndromes on quality of life in older adults: a hospital-based pilot study by Chien-Chou Su, Yung-Chen Yu, Deng-Chi Yang

“…Model performance was evaluated by 5-fold cross-validation with metrics of R-square, the mean square error of estimation and the mean absolute error of estimation. …”
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Ground data analysis for PM2.5 Prediction using predictive modeling techniques by Elham Nourmohammad, Yousef Rashidi

“…The models were evaluated based on performance metrics such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and R² scores. …”
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Predictive Factors of Length of Stay in Intensive Care Unit after Coronary Artery Bypass Graft Surgery based on Machine Learning Methods by Alireza Jafarkhani, Behzad Imani, Soheila Saeedi, Amir Shams

“…The Random Forest model also performed best in predicting the effective factors (Mean square Error = 1.64, Mean absolute error = 0.93, and R2 = 0.28) Conclusion: The insights gained from the mashine learning model highlight the significance of demographic and clinical variables in predicting LOS in ICU. …”
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Prevalence and Risk Factors for Adult Cataract in the Jingan District of Shanghai by Yingying Hong, Yang Sun, Xiaofang Ye, Yi Lu, Jianjiang Xu, Jianming Xu, Yinghong Ji

“…We provided further evidence that age and refractive error are independent cataract risk factors.…”
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QbD enabled optimization study of the variable concentration of phospholipid and stabilizer in the development of liposomal pastilles of solid dispersion polymeric composite of ant... by Deepti Agarwal, Ram Dayal Gupta, Vijay Sharma

“…Conclusion: The study showed the effectiveness of the QbD approach in optimizing a liposomal drug delivery system for FH, thereby minimizing the need for extensive trials. …”
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Evaluation of Smart Building Integration into a Smart City by Applying Machine Learning Techniques by Mustafa Muthanna Najm Shahrabani, Rasa Apanaviciene

“…The SVR-trained model substantially outperformed other models, achieving an R-squared of 0.81, Root Mean Square Error (RMSE) of 0.33 and Mean Absolute Error (MAE) of 0.27, enabling precise integration prediction. …”
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Forecasting outbound student mobility: A machine learning approach. by Stephanie Yang, Hsueh-Chih Chen, Wen-Ching Chen, Cheng-Hong Yang

“…A comparison of the FSDESVR model and other forecasting models revealed that FSDESVR provided the lowest mean absolute percentage error (MAPE) and root mean square error (RMSE) results for all the analyzed nations. …”
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Methods to quantify soft-tissue based facial growth and treatment outcomes in children: a systematic review. by Sander Brons, Machteld E van Beusichem, Ewald M Bronkhorst, Jos Draaisma, Stefaan J Bergé, Thomas J Maal, Anne Marie Kuijpers-Jagtman

“…<h4>Conclusion</h4>Various methods have shown to be reliable. …”
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Coherent Detection of Non-Orthogonal Spectrally Efficient Multicarrier Signals Using a Decision Feedback Algorithm by S. B. Makarov, S. V. Zavjalov, D. C. Nguyen, A. S. Ovsyannikova

“…The former method, although being simpler, is characterized by a low bit error rate performance. The latter method, although providing for a higher energy efficiency, is more complicated and does not allow high absolute message rates.Aim. …”
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