An Integrative Framework for Healthcare Recommendation Systems: Leveraging the Linear Discriminant Wolf–Convolutional Neural Network (LDW-CNN) Model by Vedna Sharma, Surender Singh Samant, Tej Singh, Gusztáv Fekete

“…The model’s performance is evaluated using multi-disease datasets, covering heart, liver, and kidney diseases. Established error metrics are used to compare the effectiveness of the LDW-CNN model against conventional methods, such as CNNs and multi-level support vector machines (MSVMs). …”
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Quality Metrics of Automated Machinery in Potato Plant Cultivation for Breeding and Seed Production by N. V. Sazonov, M. A. Mosyakov, V. S. Teterin, N. S. Panferov, M. M. Godyaeva, M. S. Trunov

“…This was achieved by analyzing statistical data on the distribution of the indirect parameter (indications of infection on the inside of the plant leaf) and considering the margin of error in its measurements. The reliability of the system for identifying infected plants depends on the precision of technical instruments used to gauge the plant’s condition, the methodologies employed in measurement, the software utilized for processing the obtained data, and other parameters. …”
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University proceedings. Volga region. Technical sciences by D.V. Artamonov, V.M. Myskin, A.D. Semenov

“…Parametric identification of the nonlinear heat balance equation was performed using the sliding sample method. The maximum error in calculating the emergency mode temperature using this equation does not exceed 30 C. …”

Does the FARNet neural network algorithm accurately identify Posteroanterior cephalometric landmarks? by Merve Gonca, İbrahim Şevki Bayrakdar, Özer Çelik

“…Model effectiveness was calculated by deriving the mean radial error (MRE) and the successful detection rates (SDRs) within 2, 2.5, 3, and 4 mm. …”
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Impact of Situation Awareness Variations on Multimodal Physiological Responses in High-Speed Train Driving by Wenli Dong, Weining Fang, Hanzhao Qiu, Haifeng Bao

“…Background: In safety-critical environments, human error is a leading cause of accidents, with the loss of situation awareness (SA) being a key contributing factor. …”
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Use of expert panels to define the reference standard in diagnostic research: a systematic review of published methods and reporting. by Loes C M Bertens, Berna D L Broekhuizen, Christiana A Naaktgeboren, Frans H Rutten, Arno W Hoes, Yvonne van Mourik, Karel G M Moons, Johannes B Reitsma

“…<h4>Background</h4>In diagnostic studies, a single and error-free test that can be used as the reference (gold) standard often does not exist. …”
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The impostor phenomenon among surgeons and surgeons in training: a scoping review by Chunlan Jin, Jian Ling, Zuhuan Xu, Tao Lin, Weiqin Chen

“…Abstract Background The impostor phenomenon (IP), is a condition in which people think they are incapable of success and tend to attribute their success to external causes such as luck, error, or knowing the appropriate individuals. It has been confirmed as a contributor to burnout for practicing physicians, residents, and medical students. …”
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Validation of the Nepalese Version of the Quality of Recovery-15 (QoR-N) Questionnaire in Patients Undergoing Elective Surgery by Chitra Thapa, Sabin Gauchan, Sulav Acharya, Mohan Raj Sharma

“…Results: The QoR-N showed acceptable reliability, with a Cronbach’s alpha of 0.890, mean inter-item correlation of 0.413, split-half reliability of 0.94, and standard error of measurement of 2.79. Responsiveness was supported by a Cohen’s effect size of 1.4 and standardized response mean of 1.39. …”
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The cultural validation of two scales to assess social stigma in leprosy. by Ruth M H Peters, Dadun, Wim H Van Brakel, Marjolein B M Zweekhorst, Rita Damayanti, Joske F G Bunders, Irwanto

“…The exploratory factor analysis indicated for both scales an adequate fit as unidimensional scale. A standard error of measurement of 2.38 was found in the EMIC-CSS and of 1.78 in the SDS. …”
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The Reliability and Validity of a Novel Clinical Test for Assessing Shoulder Rotation ROM in Collegiate Baseball Players: Functional Assessment of System Tension of the Shoulder (F... by Steven Dischiavi, Jesse Perry, Connor Burk, Jeremy Chiang, Chris Bleakley

“…Intra-class correlation coefficient (ICC), standard error of measurement (SEM) and minimum detectable change (MDC) were calculated. …”
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Age estimation from morphometric features of maxillary central incisors using CBCT images by Sara Hilmi Kazzaz, Tavga Mustafa Faris, Miwan Salahalddin Abdulrahman, Mohammed Taha Ahmed Baban, Ranjdar Mahmood Talabani, Kazhan Omer Abdalrahman

“…In males, the equation derived from multiplanar linear measurements demonstrated a standard error of estimate (SEE) of ± 10.84 years, with a coefficient of determination (R²) of 0.49. …”
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An ensemble prediction approach to weekly Dengue cases forecasting based on climatic and terrain conditions by Sougata Deb, Cleta Milagros Libre Acebedo, Gomathypriya Dhanapal, Chua Matthew Chin Heng

“…Results: The proposed ensemble prediction achieved a mean absolute error of 21.55, 4.26 points lower than the 25.81 obtained by a standard negative binomial model. …”
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Specificity Analysis of Genome Based on Statistically Identical K-Words With Same Base Combination by Hyein Seo, Yong-Joon Song, Kiho Cho, Dong-Ho Cho

“…In order to find important ratios representing genomic characteristics, a reference value is calculated that results in a minimum error when classifying data by ratio alone. Finally, we propose a genetic algorithm-based search algorithm to select a minimum set of ratios useful for classification. …”
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Enhanced Electroacoustic Tomography with Supervised Learning for Real‐time Electroporation Monitoring by Zhuoran Jiang, Yifei Xu, Leshan Sun, Shreyas Srinivasan, Q. Jackie Wu, Liangzhong Xiang, Lei Ren

“…Quantitatively, the enhanced single‐view images achieved a low‐intensity error (RMSE: 0.018), high signal‐to‐noise ratio (PSNR: 35.15), and high structural similarity (SSIM: 0.942) compared to the reference full‐view images. …”
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Determination of the dynamic characteristics of a gear pump by the load variation method using special bench systems by V. I. Sanchugov, P. D. Rekadze

“…The bench systems yielding the calculation of the dynamic characteristics of the pump with a minimum error based on the condition of matching the dynamic load and the source of vibrations were analyzed. …”
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Allocating the Sample Size in Phase II and III Trials to Optimize Success Probability by Daniele De Martini

“…</p><p>{\bf Results} For example, when 5 doses are evaluated in phase II and 2 parallel phase III confirmatory trials (one-tail type I error $=2.5\%$, power $=90\%$) are considered with 2 groups each, $k=24$ is needed to obtain $OSP\simeq 75\%$, with $r_{opt}\simeq 50\%$. …”
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Investigation of Antibody Pharmacokinetics in Male Reproductive System and Its Characterization Using a Translational PBPK Model by Sree Ojili, Dhaval K. Shah

“…All the predicted PK profiles were within two-fold of the observed data, as indicated by percentage prediction error (%PE) values. The mouse model was successfully translated to bigger animals, and the model was used to simulate the PK of antibodies in rat, monkey, and human male reproductive systems. …”
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Performance of the Direct Sequence Spread Spectrum Underwater Acoustic Communication System with Differential Detection in Strong Multipath Propagation Conditions by Jan H. SCHMIDT, Iwona KOCHAŃSKA, Aleksander M. SCHMIDT

“…Both, m-sequences and Kasami codes allow to achieve a similar bit error rate, which at best was less than 10−3. At the same time, the 6th order sequences are not long enough to achieve an acceptable BER under strong multipath conditions. …”
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Measurement of level of PTSD with the International Trauma Questionnaire (ITQ): bias and precision when using full ordinal or dichotomized items by Tine Nielsen, Ask Elklit, Sabrina Brødsgaard Nielsen, Mikkel Auning-Hansen, Svend Kreiner, Maria Louison Vang

“…Measurement by scores over dichotomized items increased the standard error of measurement and reduced the reliability to a level, where psychometric theory would conclude that the measure of PTSD was inapplicable. …”
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Crop Yield Prediction: Data Structure and Ai-Powered Methods by V. K. Kalichkin, K. Yu. Maksimovich, O. A. Aleshchenko, V. V. Aleshchenko

“…Comparative analysis demonstrates that deep learning and hybrid approaches outperform traditional machine learning methods in terms of prediction accuracy, as measured by standard error metrics. (Conclusions) The findings confirm the advantages of deep learning methods (mean R² = 0.85) and hybrid approaches (mean R² = 0.87) in crop yield prediction under varying conditions and management interventions. …”
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