Reading and Interpreting Recommendations for the Nahj al-Farādīs by Samet Onur

“…This study focuses mainly on copying, pointing, reading and interpretation errors that can lead to misunderstandings of the text, ghost words or meanings, and misinterpretations of the phonetic and morphological characteristics of the period. …”
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Tuberculosis Immunodiagnosis System: Analysis of Potential Losses of Patients for Registration by S. A. Sterlikov, T. N. Kаzykinа

“…The objective: to develop proposals to improve the effectiveness of the tuberculosis immunodiagnosis system in children by analyzing potential losses of patients for registration.Materials: data from primary medical records of 605 children in 5 regions of Russia, results of the survey in 513 legal guardians and 27 experts.Results. 13.9% of the children subject for screening were not examined, tests were administered in 1.1% of children who had contraindications to them, errors in the test administration were expected in 1.5% of children, and in 6.2% of children, antihistamine medications were used leading to errors in the detection of tuberculosis infection. …”
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DYNAMICS OF HIGHER MENTAL FUNCTION CHANGES IN CHILDREN AND ADOLESCENTS WITH PARTIAL FORMS OF EPILEPSY IN CLINICAL REMISSION by Tinatin Yuzovna Gogberashvili, Y. V. Mikadze

“…The most frequent and pronounced disorders in the primary examination were spatial, kinesthetic and constructive praxis disorders, visual-spatial and acoustic-nonvoice gnosis disorders, increased inhibition of traces, audio-verbal and visual memory constriction, defective order of reproducing words (figures) in stimulus sequence (transient errors), spatial errors in visual-constructive thinking, paragraphia. …”
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Polymorphism of ABO*O alleles and its clinical significance by L. L. Golovkina, R. S. Kalandarov, O. S. Pshenichnikova, V. L. Surin, A. G. Stremoukhova, T. D. Pushkina, G. V. Atroshchenko, O. S. Kalmykova, B. B. Khasigova

“…Some ABO*O alleles may be accompanied by the presence of residual A-glycosyltransferase activity in people of group O, which may lead to errors in determining the blood group. This confirms the important clinical significance of the ABO*O allele polymorphism. …”
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Capabilities of the WRF-Chem model in estimating the concentration of dust – A case study of a dust storm in Tehran by Amirhossein Nikfal, Abbas Ranjbar Saadatabadi, Sara Karami, Saviz Sehatkashani

“…Because of some limitations in the MADE aerosol scheme for the regions with high topographical features, its results might show over- and/or underestimations. Also if there are errors in the land use data and the erosion properties of soil, the model results may show a discrepancy from the real measurements. …”
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Impact of CT-based navigation, large femoral head, and dual-mobility liner on achieving the required range of motion in total hip arthroplasty by Toshiki Konishi, Satoshi Hamai, Shinya Kawahara, Daisuke Hara, Taishi Sato, Goro Motomura, Takeshi Utsunomiya, Yasuharu Nakashima

“…We compared the absolute errors for radiological inclination (RI) and radiological anteversion (RA) between the two groups. …”
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Enhanced data quality to improve malaria surveillance in Papua, Indonesia by Liony Fransisca, Faustina Helena Burdam, Enny Kenangalem, Annisa Rahmalia, Reynold Rizal Ubra, Christel H. A. van den Boogaard, Benedikt Ley, Nicholas M. Douglas, Jeanne Rini Poespoprodjo, Ric N. Price

“…The second CQI round reduced DHP prescribing errors from 17.1% (1111/6489) in the initial period to 5.7% (607/10,669) after the second CQI (Sep 2019–Jan 2020) and PQ prescribing errors from 17.4% (552/3175) to 3.4% (160/4659) over the same time interval, p < 001. …”
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The Development of a Non-Invasive Screening Method Based on Serum microRNAs to Quantify the Percentage of Liver Steatosis by Polina Soluyanova, Guillermo Quintás, Álvaro Pérez-Rubio, Iván Rienda, Erika Moro, Marcel van Herwijnen, Marcha Verheijen, Florian Caiment, Judith Pérez-Rojas, Ramón Trullenque-Juan, Eugenia Pareja, Ramiro Jover

“…External validation of this model with a cohort of mixed MASLD patients (<i>n</i> = 25) showed a root mean squared error of prediction (RMSEP) of 5.3. In conclusion, it is possible to predict the percentage of hepatic steatosis with a low error rate by quantifying the serum level of five miRNAs using a cost-effective and easy-to-implement RT-qPCR method.…”
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Analytical estimation of influence of dynamic parameters of testing machine fluid drive on accuracy of test operations by D. N. Andrianov, N. V. Andrianov

“…There are given conclusions and recommendations on reducing of test operations error.…”
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Design and psychometric properties of a tool to assess Adherence to the Code of Ethics in Midwifery by Zahra Kiani, Masoumeh Simbar, Abbas Ebadi, Soheila Nazarpour

“…Absolute reliability was also measured by calculating the standard error of measurement (SEm) and minimum detectable change (MDC) indexes. …”
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The PERFORM Study: Artificial Intelligence Versus Human Residents in Cross-Sectional Obstetrics-Gynecology Scenarios Across Languages and Time Constraints by Canio Martinelli, MD, Antonio Giordano, MD, Vincenzo Carnevale, PhD, Sharon Raffaella Burk, PhD, Lavinia Porto, MD, Giuseppe Vizzielli, MD, Alfredo Ercoli, MD

“…Objective: To systematically evaluate the performance of artificial intelligence (AI) large language models (LLMs) compared with obstetrics-gynecology residents in clinical decision-making, examining diagnostic accuracy and error patterns across linguistic domains, time constraints, and experience levels. …”
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Epidemiological Assessment and Inference in Race-Based Clinical Algorithms: A Narrative Review and Health Policy Analysis Focused on Living Kidney Donation by Sienna E. Schaeffer, Carolina Gonzalez Bravo, Christopher D. Ahlers, Alaina N. Elliott-Wherry, Hannah Zadeh, Precious-Junia de-Winton Cummings, Kimberly C. Dukes, Nasrien E. Ibrahim, DeShauna Jones, Patrick T. Zamba, Aloha D. Wilks, Martha L. Carvour

“…We also identified structural barriers to the interpretation of this evidence to advance health equity, including barriers to the practices of clinical equipoise and shared medical decision-making. Conclusions: Threats to scientific validity and inferential errors in the evidence base about health inequities may forestall progress toward equity. …”
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Comparative Analysis of Atlas and Neural Network Autosegmentation Methods for Pediatric Craniospinal Irradiation With the Development of a Knowledge-Based Quality Assurance Tool by Ozgur Ates, James Man Git Tsui, Zachary Wooten, Sydney Hutcheson, Rico Zhang, Jared Becksfort, Thomas E. Merchant, Chia-ho Hua

“…Furthermore, a knowledge-based QA tool enables clinicians to detect and correct gross errors in autosegmentation.…”
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To Stitch or Not to Stitch, That Is the Question: Multi-Gaze Eye Topography Stitching Versus Single-Shot Profilometry by Wen-Pin Lin, Lo-Yu Wu, Wei-Ren Lin, Lynn White, Richard Wu, Arwa Fathy, Rami Alanazi, Jay Davies, Ahmed Abass

“…Close eye rotations were found in the right-gaze, left-gaze and up-gaze directions, with rotation angles of around 8°; however, the down-gaze angle was around 15°, almost twice other gaze rotation angles. Root mean squared error (RMSE) analysis revealed notable discrepancies, particularly in the right-, left-, and up-gaze directions, with errors reaching up to 98 µm compared to ESP scans. …”
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Comparing IOL refraction prediction accuracy and A-constant optimization for cataract surgery patients across South Indian and Midwestern United States populations by Omer Siddiqui, Elisa Warner, Miles Greenwald, Tingyang Li, Karthik Srinivasan, Aravind Haripriya, Nambi Nallasamy

“…Seven IOL formulas were applied to predict postoperative refraction, and performance was assessed by comparing mean absolute errors both before and after population-specific A-constant optimization. …”
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Learning Curves in Laparoscopic Training: Comparative Analysis of Two Training Models by Layla Settaf-Cherif, Adam Ostrowski, Anmol Khan, Katarzyna Malinowska, Oliwia Kwiatkowska, Łukasz Paszylk, Jan Adamowicz, Tomasz Drewa

“…One month follow-up evaluations showed significantly shorter task times completion in the distributed group for peg transfer (p=0.014, d=1.97) and cutting a circle (p=0.036, d=1.74). Conclusions: Distributed training demonstrated superiority in skill retention, error reduction, and consistent task performance, especially in tasks requiring precision. …”
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Experimental Investigation of Liquid Pressure in a Straight Circular Cross-Section Pipeline by Vafaeva Khristina Maksudovna, Karpov Denis Fedorovich, Pavlov Mikhail Vasilyevich, Baloji Dharavath, Sharma Pratibha, Deorari Rajesh, Bhatnagar Sanjay, Kalpana Kasapogu, Gudainiyan Jitendra

“…The absolute and relative errors of indirect technical measurements of linear pressure losses due to friction in the pipeline were approximately ≈1.04 Pa and ≈10.6 %, respectively. …”
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Reliability of trachoma clinical grading--assessing grading of marginal cases. by Salman A Rahman, Sun N Yu, Abdou Amza, Sintayehu Gebreselassie, Boubacar Kadri, Nassirou Baido, Nicole E Stoller, Joseph P Sheehan, Travis C Porco, Bruce D Gaynor, Jeremy D Keenan, Thomas M Lietman

“…Here, we confirm those results and assess performance of trainees on these borderline cases by calculating their reliability error, a measure derived from the decomposition of the Brier score.…”
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Comparative analysis of machine learning algorithms for predicting tibial intramedullary nail length from patient characteristics by Yujian Hui, Hengda Hu, Jinghua Xiang, Xingye Du

“…Models were trained and evaluated using root mean squared error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and correlation analysis. …”
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Interval Prediction Method for Solar Radiation Based on Kernel Density Estimation and Machine Learning by Meiyan Zhao, Yuhu Zhang, Tao Hu, Peng Wang

“…The performance of interval prediction methods is evaluated by the prediction interval coverage probability (PICP), prediction interval normalized average width (PINAW), and coverage width criteria (CWC). The following conclusions are drawn from this study. First, the V-SVR model performs best with the lowest mean absolute error (MAE) of 0.016 and mean relative error (MRE) of 0.001. …”
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