Multi-scale attention patching encoder network: a deployable model for continuous estimation of hand kinematics from surface electromyographic signals by Chuang Lin, Qiong Xiao, Penghui Zhao

“…Furthermore, we tested the deployment performance of sMAPEN on the portable device, with a delay of only 97.93 ms. Conclusions Our model can predict up to 40 hand movements while achieving the highest predicting accuracy compared with other methods. …”
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Unraveling trends in schistosomiasis: deep learning insights into national control programs in China by Qing Su, Cici Xi Chen Bauer, Robert Bergquist, Zhiguo Cao, Fenghua Gao, Zhijie Zhang, Yi Hu

“…Two traditional models were also constructed for comparison with 2 evaluation indicators: the mean-squared prediction error (MSPE) and continuous ranked probability score (CRPS). …”
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Directed evolution of α-ketoisovalerate decarboxylase for improved isobutanol and 3-methyl-1-butanol production in cyanobacteria by Hao Xie, Afshan Begum, Laura H. Gunn, Peter Lindblad

“…This screen was coupled with random mutagenesis, via error-prone PCR, of KivdS286T. Out of the 1600 variants, 1B12, featuring dual substitutions K419E and T186S, exhibited a 55% increase in IB production and a 50% increase in 3M1B production in Synechocystis on the fourth day of cultivation. …”
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Can linear regression modeling help clinicians in the interpretation of genotypic resistance data? An application to derive a lopinavir-score. by Alessandro Cozzi-Lepri, Mattia C F Prosperi, Jesper Kjær, David Dunn, Roger Paredes, Caroline A Sabin, Jens D Lundgren, Andrew N Phillips, Deenan Pillay, EuroSIDA Study, United Kingdom CHIC/United Kingdom HDRD Study

“…All models performed equally well (ASE on test ranging between 1.1 and 1.3, p = 0.34).<h4>Conclusions</h4>We fully explored the potential of linear regression to construct a simple predictive model for lopinavir/r-based TCE. …”
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Data measurement system for non-destructive quality testing of hard alloys by I. K. Tsybrii, I. L. Vyalikov, V. I. Ignatenko

“…Providing that the relative error of measuring the coercitive force for each sample should be within ± 6%, the results obtained can be considered satisfactory. …”
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Milky Way Dark Matter Distribution or MOND Test from Vertical Stellar Kinematics with Gaia DR3 by Martín López-Corredoira

“…Similarly, for R > R _⊙ , z = 1.05 kpc, Σ = 28.7 ± 9.6, 23.0 ± 5.7, 16.9 ± 5.8, and 11.4 ± 6.6 M _⊙ pc ^−2 , respectively, for R = 10, 13, 16, and 19 kpc, compatible with visible matter alone. Larger error bars in comparison with previous works are not due to worse data or a more awkward technique but to a stricter modeling of the stellar distribution.…”
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Fast estimation of patient‐specific organ doses from abdomen and head CT examinations without segmenting internal organs using machine learning models by Wencheng Shao, Liangyong Qu, Xin Lin, Ying Huang, Weihai Zhuo, Haikuan Liu

“…The accuracy of the models was evaluated using the mean absolute percentage error (MAPE) and coefficient of determination (R2). …”
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Predictive nomogram of high-risk patients with active tuberculosis in latent tuberculosis infection by Kui Li, Siyi Liu, Yingli He, Renyu Ran

“…Internal validation showed a mean absolute error of 0.013 and 86.4% identification accuracy. …”
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Chemical genetic inhibition of Mps1 in stable human cell lines reveals novel aspects of Mps1 function in mitosis. by Tale Sliedrecht, Chao Zhang, Kevan M Shokat, Geert J P L Kops

“…Timed inhibition during bipolar spindle assembly shows that Mps1 is critical for attachment error-correction and confirms its role in Aurora B regulation. …”
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Estimation of Three-Dimensional Ground Reaction Force and Center of Pressure During Walking Using a Machine-Learning-Based Markerless Motion Capture System by Ru Feng, Ukadike Christopher Ugbolue, Chen Yang, Hui Liu

“…For the COP estimation, the r-values for MLP ranged from 0.727 to 0.982, with rRMSEs between 6.43% and 27.64%, while the r-values for CNN ranged from 0.896 to 0.977, with rRMSEs between 6.41% and 7.90%. Conclusions: It is possible to estimate GRF and COP from markerless motion capture data. …”
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Designing a portable and accessible diffuse reflectance spectroscopy system for real-time detection of cervical intraepithelial neoplasia by Allison Scarbrough, Diana Moses, Tongtong Lu, Bing Yu

“…Phantom [Formula: see text] and [Formula: see text] were predicted with average root-mean square error of [Formula: see text], regardless of user. …”
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Translation, cross-cultural adaptation and validation of the Weight Management Questionnaire in the Brazilian population: a cross-sectional study by Brígida Rodrigues da Costa, Almir Vieira Dibai-Filho, Aldair Darlan Santos-de-Araújo, Fábio Henrique Ferreira Pereira, Daniela Bassi-Dibai, Adriana Sousa Rêgo

“…We observed adequate reliability for both domains (ICC ≥ 0.854). CONCLUSIONS: The WMQ can be used for the Brazilian population, as it is reliable and has adequate internal structure, supporting its use in future research.…”
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Predicting fall risk in older adults: A machine learning comparison of accelerometric and non-accelerometric factors by Ana González-Castro, José Alberto Benítez-Andrades, Rubén González-González, Camino Prada-García, Raquel Leirós-Rodríguez

“…Performance was evaluated based on mean squared error (MSE) and coefficient of determination ( R 2 ), to assess how combining multiple data types influences prediction accuracy. …”
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Psychometric evaluation of the Persian version of the adult chronic kidney disease self-management instrument in the Iranian population by Simin Alasvand, Mehrnaz Ahmadi, Hamid Sharif-Nia, Marziyeh Asadizaker

“…The absolute reliability, as determined by Standard Error of Measurement results, was 3.16. Additionally, the Minimum Detectable Change was estimated to be 8.75. …”
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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

“…(Conclusions) Measurement information management involves making a judicious selection of an indirect parameter that guarantees the precision of identifying infected plants with a confidence interval of 0.95. …”
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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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