Enhancing Supply Chain Resilience Through Artificial Intelligence: Developing a Comprehensive Conceptual Framework for AI Implementation and Supply Chain Optimization by Meriem Riad, Mohamed Naimi, Chafik Okar

“…Furthermore, I-driven automation and robotics enhance operational efficiency by minimizing human error and streamlining processes. <i>Methodology/Approach</i>: This paper proposes a conceptual framework for strengthening supply chain resilience through AI integration. …”
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Measurement-guided therapeutic-dose prediction using multi-level gated modality-fusion model for volumetric-modulated arc radiotherapy by Changfei Gong, Changfei Gong, Changfei Gong, Yuling Huang, Yuling Huang, Yuling Huang, Junming Jian, Junming Jian, Junming Jian, Wenheng Zheng, Wenheng Zheng, Wenheng Zheng, Xiaoping Wang, Xiaoping Wang, Xiaoping Wang, Shenggou Ding, Shenggou Ding, Shenggou Ding, Yun Zhang, Yun Zhang, Yun Zhang

“…Quantitative experimental predictions show that the proposed model achieved the lowest values for the mean absolute error (37.99) and root mean square error (4.916), and the highest values for the peak signal-to-noise ratio (52.622), structural similarity (0.986) and universal quality index (0.932). …”
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Development of an approach to forecast future takeaway outlet growth around schools and population exposure to takeaways in England by Bochu Liu, Oliver Mytton, John Rahilly, Ben Amies-Cull, Nina Rogers, Tom Bishop, Michael Chang, Steven Cummins, Daniel Derbyshire, Suzan Hassan, Yuru Huang, Antonieta Medina-Lara, Bea Savory, Richard Smith, Claire Thompson, Martin White, Jean Adams, Thomas Burgoine

“…Forecast performance was evaluated based on root mean squared error (RMSE) and mean absolute scaled error (MASE) scores in time-series cross-validation. …”
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Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models by Qing Zhang, Qi Li, Zhilong Yu, Ruibo Yang, Emmanuel Eric Pazo, Yue Huang, Hui Liu, Chen Zhang, Salissou Moutari, Shaozhen Zhao

“…Model performance was evaluated using metrics including the mean absolute error (MAE) and root mean squared error (RMSE) for regression models, while accuracy, F1-score, and area under the curve (AUC) were used for classification models. …”
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Investigating the Neural Mechanisms of Self-Controlled and Externally Controlled Movement with a Flexible Exoskeleton Using EEG Source Localization by Takayuki Kodama, Masahiro Yoshikawa, Kosuke Minamii, Kazuhei Nishimoto, Sayuna Kadowaki, Yuuki Inoue, Hiroki Ito, Hayato Shigeto, Kohei Okuyama, Kouta Maeda, Osamu Katayama, Shin Murata, Kiichiro Morita

“…Source localization revealed that self-controlled tasks engaged motor planning and error-monitoring regions more robustly. Conclusions: The flexEXO device and the comparison of brain activity under different conditions provide insights into the neural mechanisms of motor control and have implications for neurorehabilitation.…”
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Mountain Landslide Monitoring Using a DS-InSAR Method Incorporating a Spatio-Temporal Atmospheric Phase Screen Correction Model by Shipeng Guo, Xiaoqing Zuo, Jihong Zhang, Xu Yang, Cheng Huang, Xuefu Yue

“…We conducted tests on 28 full-resolution SENTINEL-1A images to validate the effectiveness of our methods. The conclusions are as follows: (1) Under the same sample conditions, confidence interval estimation demonstrated higher performance in identifying SHPs compared to generalized likelihood ratio test. …”
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The Number of Microbubbles Generated During Cardiopulmonary Bypass Can Be Estimated Using Machine Learning From Suction Flow Rate, Venous Reservoir Level, Perfusion Flow Rate, Hema... by Satoshi Miyamoto, Zu Soh, Shigeyuki Okahara, Akira Furui, Taiichi Takasaki, Keijiro Katayama, Shinya Takahashi, Toshio Tsuji

“…Conclusions: Our results highlight the potential of this system to improve patient outcomes and reduce MB-associated complication risk.…”
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Reliability of Sensorimotor Control Tests in Individuals with Adolescent Idiopathic Scoliosis by Alexandros Kastrinis, Nikolaos Strimpakos, George A. Koumantakis, Dionysios Tzatzaliaris, Marianna Oikonomaki, Evangelos Theodosopoulos, Evangelia Skaftourou, Maria Tsekoura, Asimakis K. Kanellopoulos, Eleni Nomikou, Zacharias Dimitriadis

“…Reliability was measured using the intraclass correlation coefficient (ICC), standard error of measurement (SEM), and smallest detectable difference (SDD). …”
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Variation of Main Phenophases in Phenological Calendar in East China and Their Response to Climate Change by Fengyi Zheng, Zexing Tao, Yachen Liu, Yunjia Xu, Junhu Dai, Quansheng Ge

“…We calculated the correlated coefficient and the root mean square error (RMSE) between phenophases and the beginning of meteorological seasons to determine the beginning date of phenological season. …”
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Is there a role for nutritional advice during breastfeeding for infant colic relief? A mixed-method study by Belén Vázquez, Michelle Barrow, James Neil, Karin Seidler

“…When dietary change brought relief to the baby, it turned into a coping tool for women facilitating extended breastfeeding. Conclusions: Maternal dietary change can play a positive role in providing relief to breastfed babies with colic. …”
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Subject-Independent Cuff-Less Blood Pressure Monitoring via Multivariate Analysis of Finger/Toe Photoplethysmography and Electrocardiogram Data by Seyedmohsen Dehghanojamahalleh, Peshala Thibbotuwawa Gamage, Mohammad Ahmed, Cassondra Petersen, Brianna Matthew, Kesha Hyacinth, Yasith Weerasinghe, Ersoy Subasi, Munevver Mine Subasi, Mehmet Kaya

“…A multivariate regression model was employed to estimate BP. (3) Results: The results showed that incorporating toe PPG signals improved the accuracy of BP estimation, reducing the mean absolute error (MAE). Using both finger and toe PPG signals resulted in an MAE of 9.63 ± 12.54 mmHg for systolic BP and 6.76 ± 8.38 mmHg for diastolic BP, providing the lowest MAE compared to previous methods. (4) Conclusions: This study is the first to integrate toe PPG for more accurate BP estimation and proposes a method that does not require an initial cuff-based BP measurement, offering a promising approach for non-invasive, continuous BP monitoring.…”
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A Novel Concept of the “Standard Human” in the Assessment of Individual Total Heart Size: Lessons from Non-Contrast-Enhanced Cardiac CT Examinations by Maciej Sosnowski, Zofia Parma, Marcin Syzdół, Grzegorz Brożek, Jan Harpula, Michał Tendera, Wojciech Wojakowski

“…Differences were found to be sex-independent in all BMI categories. <b>Conclusions:</b> Common BSA correction hides these differences and makes the prognostication of CV risk error-introducing. …”
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Evaluation of Subfoveal Choroidal Thickness in Internal Carotid Artery Stenosis by Betül İlkay Sezgin Akçay, Esra Kardeş, Sultan Maçin, Cihan Ünlü, Engin Bilge Özgürhan, Aydın Maçin, Tahir Kansu Bozkurt, Ahmet Ergin, Reyhan Surmeli

“…The two groups were compared in terms of the percentage of stenosis, SFCT measurements, intraocular pressure, ocular perfusion pressure, refractive error, and peak systolic velocity. Eyes were examined with the RTVue-100 OCT device by the EDI-OCT technique. …”
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Expansion of genotypic and phenotypic findings in ADAMTS18-related ocular pathology by Ari H. August, Rebecca A. Procopio, Christopher J. Rapuano, José S. Pulido

“…Features include distinctive facies, refractive error, anterior segment dysgenesis, and retinal dystrophy. …”
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Video-Based Assessment of Surgical Skill in Orthopaedic Surgery by Jillian McNally, MD, David Wilson, MD, MSc, FRCSC, Emma E. Jones, BScH, Neyousha Shahisavandi, MPH, Caroline King, PhD, Chad Coles, MD, FRCSC, Raymond Andrew Glennie, MD, MSc, FRCSC

“…A larger, multicentered study with more participants is needed to draw any further conclusions.…”
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Eradication of Helicobacter pylori for prevention of aspirin-associated peptic ulcer bleeding in adults over 65 years: the HEAT RCT by CJ Hawkey, Anthony J Avery, Carol AC Coupland, Colin J Crooks, Jennifer S Dumbleton, FD Richard Hobbs, Denise Kendrick, Michael Moore, Clive Morris, Gregory Rubin, Murray Smith, Diane Stevenson

“…Omitting mention of death due to peptic ulcer bleeding from the protocol was an error, but it did not affect the analysis, as there were no pre-hospitalisation deaths. …”
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Improved epigenetic age prediction models by combining sex chromosome and autosomal markers by Zhong Wan, Peter Henneman, Huub C. J. Hoefsloot, Ate D. Kloosterman, Pernette J. Verschure

“…Cross-validation of the constructed RFR models using more than 10,000 X and 30 Y chromosomal DNAm markers from all collected blood samples, provided a root-mean squared error (RMSE) ranging from 7.70 to 14.29 years, and a mean absolute deviation (MAD) from 6.10 to 11.13 years. …”
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Application of Isokinetic Dynamometry Data in Predicting Gait Deviation Index Using Machine Learning in Stroke Patients: A Cross-Sectional Study by Xiaolei Lu, Chenye Qiao, Hujun Wang, Yingqi Li, Jingxuan Wang, Congxiao Wang, Yingpeng Wang, Shuyan Qie

“…Model performance was evaluated using mean squared error (MSE), the coefficient of determination (R²), and mean absolute error (MAE). …”
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Estudio sobre la idoneidad de dos test de valoración de la amplitud de movimiento en personas sedentarias con discapacidad intelectual (Study on the suitability of two test for th... by Ruth Cabeza-Ruiz, Pedro Tomás Gómez Piriz

“…Para conocer la idoneidad de ambos test, se calculó la fiabilidad, la viabilidad, el error estándar de la medida (EEM) y el mínimo cambio detectable (MCD). …”
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Validation of Deep Learning–Based Automatic Retinal Layer Segmentation Algorithms for Age-Related Macular Degeneration with 2 Spectral-Domain OCT Devices by Souvick Mukherjee, PhD, Tharindu De Silva, PhD, Cameron Duic, BS, Gopal Jayakar, BS, Tiarnan D.L. Keenan, BM BCh, PhD, Alisa T. Thavikulwat, MD, Emily Chew, MD, Catherine Cukras, MD, PhD

“…Main Outcome Measures: Performance metrics (including mean squared error, mean absolute error [MAE], and Dice coefficients) for the segmentations of the internal limiting membrane (ILM), retinal pigment epithelium (RPE), and RPE to Bruch’s membrane region, along with en face thickness maps, volumetric estimations (in mm3). …”
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