Incorporating Contextual Factors into a Comprehensive Analysis of Operational Efficiency and Service Quality in Healthcare Sector by Utsav Pandey, Sanjeet Singh

“…While accounting for the external influences and avoiding the ‘best practice trap’ in the healthcare sector, a set of classification algorithms are used to quantify the impact of external factors on efficiency levels. …”
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Net buffer load during regional citrate anticoagulated continuous renal replacement therapy. by Innas Forsal, Dominique Pouchoulin, Viktoria Roos, Jorge Echeverri, Marcus Ewert Broman

“…This parameter is integrated as a static safety parameter in the Prismax version 3 software, and will guide the operator on a possible development of metabolic alkalosis with the current settings.<h4>Methods</h4>Algorithms for estimating the net buffer load were developed. …”
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Solving the Fragment Complexity of Official, Social, and Sensorial Urban Data by Hui Liu, Jingqing Jiang, Yaowei Hou, Jie Song

“…In this paper, the index architecture, logical structure and algorithms, the implementation details, the creation process, the integration to the existing key-value store, and the urban application scenario are described. …”
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Judges versus artificial intelligence in juror decision-making in criminal trials: Evidence from two pre-registered experiments. by Eiichiro Watamura, Yichen Liu, Tomohiro Ioku

“…These findings suggest that jurors do not inherently avoid algorithmic judgments and may consider AI opinions on par with those of human judges in certain contexts. …”
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Influence of Intraoral Scanners, Operators, and Data Processing on Dimensional Accuracy of Dental Casts for Unsupervised Clinical Machine Learning: An In Vitro Comparative Study by Taseef Hasan Farook, Saif Ahmed, Jamal Giri, Farah Rashid, Toby Hughes, James Dudley

“…However, data augmentation was crucial for processing intraoral scans in deep learning algorithms, introducing structural differences in the 3D scans. …”
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Subgraph-Indexed Sequential Subdivision for Continuous Subgraph Matching on Dynamic Knowledge Graph by Yunhao Sun, Guanyu Li, Mengmeng Guan, Bo Ning

“…Finally, extensive empirical studies on real and synthetic graphs demonstrate that our techniques outperform the state-of-the-art algorithms.…”
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Designing and planning a bioethanol supply chain network under uncertainty using a data-driven robust optimization model under disjunctive uncertainty sets by Farzaneh MansooriMooseloo, Maghsoud Amiri, Mohammad Taghi Taghavi Fard, Mostafa Hajiaghaei-Keshteli

“…Therefore, the aim of this study is to design and optimize the biomass-to-bioethanol supply chain network using data-driven robust optimization methods and disjunctive uncertainty sets.Methodology: The methodology of this study is a multi-methodology approach based on mathematical modeling and machine learning algorithms. Initially, uncertainty sets for the non-deterministic model parameter were created using K-means and SVC methods. …”
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AI-Based Holistic Framework for Cyber Threat Intelligence Management by Arnolnt Spyros, Ilias Koritsas, Angelos Papoutsis, Panos Panagiotou, Despoina Chatzakou, Dimitrios Kavallieros, Theodora Tsikrika, Stefanos Vrochidis, Ioannis Kompatsiaris

“…Furthermore, the proposed framework leverages the MISP platform for storing, enriching and sharing while also integrating Artificial Intelligence (AI) and Machine Learning (ML) algorithms for advanced data enrichment.…”
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Maximizing Energy Output of Photovoltaic Systems: Hybrid PSO-GWO-CS Optimization Approach by Hassan S. Ahmed, Ahmed J. Abid, Adel A. Obed, Ameer L. Saleh, Reheel J. Hassoon

“…Based on these results, a hybrid mode of merging algorithms based on weather radiation conditions is proposed. …”
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Applying the Block-Based Programming Language ALICE for Developing Programming Competencies in University Students by Mariuxi Vinueza-Morales, Jesennia Cardenas-Cobo, Jessica Cabezas-Quinto, Cristian Vidal-Silva

“…The information society is part of modern life, and algorithmic thinking and programming are relevant to everybody, regardless of educational background. …”
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Association between cardiopulmonary bypass duration and early major adverse cardiovascular events after surgical repair of supravalvular aortic stenosis by Simeng Zhang, Caiyi Wei, Bo Peng, Lizhi Lv, Fengbo Pei, Jianming Xia, Jun Yan, Jie Liu, Qiang Wang, Yi Shi

“…Consistent results were obtained in the Inverse probability of treatment-weighted, standardized mortality ratio-weighted, pairwise algorithmic-weighted, and overlap-weighted models.ConclusionPatients with CPB duration &gt;2 h were at a higher risk of early postoperative MACE compared to those with CPB duration ≤2 h. …”
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Microwave sea ice and ocean brightness temperature and emissivity between 22 and 243 GHz from ship-based radiometers by Janna E. Rückert, Andreas Walbröl, Nils Risse, Pavel Krobot, Rainer Haseneder-Lind, Mario Mech, Kerstin Ebell, Gunnar Spreen

“…Our results can improve the characterization of surface emissions in satellite retrieval algorithms.…”
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A Novel Active Learning Technique for Fetal Health Classification Based on XGBoost Classifier by Kaushal Bhardwaj, Niyati Goyal, Bhavika Mittal, Vandna Sharma, Shiv Naresh Shivhare

“…The application of machine learning algorithms in monitoring fetal health helps to improve the chances of timely intervention and better outcomes in the event of any possible health issues in fetuses. …”
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Predictive model for abdominal liposuction volume in patients with obesity using machine learning in a longitudinal multi-center study in Korea by Hyunji Sang, Jaeyu Park, Soeun Kim, Myeongcheol Lee, Hojae Lee, Sun-Ho Lee, Dong Keon Yon, Sang Youl Rhee

“…Fifteen variables related to patient profiles were integrated and applied to various ML algorithms, including random forest, support vector, XGBoost, decision tree, and AdaBoost regressors. …”
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Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology by Matteo P. Ferla, Rubén Sánchez-García, Rachael E. Skyner, Stefan Gahbauer, Jenny C. Taylor, Frank von Delft, Brian D. Marsden, Charlotte M. Deane

“…Abstract Current strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens generally do not fully leaverage 3D structural information. We show that an algorithmic approach (Fragmenstein) that ‘stitches’ the ligand atoms from this structural information together can provide more accurate and reliable predictions for protein–ligand complex conformation than general methods such as pharmacophore-constrained docking. …”
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Prevention and management of degenerative lumbar spine disorders through artificial intelligence-based decision support systems: a systematic review by Paolo Giaccone, Federico D’Antoni, Fabrizio Russo, Luca Ambrosio, Giuseppe Francesco Papalia, Onorato d’Angelis, Gianluca Vadalà, Albert Comelli, Luca Vollero, Mario Merone, Rocco Papalia, Vincenzo Denaro

“…Several different machine learning and deep learning algorithms were employed, and their predictive ability on clinical, demographic, psychosocial, and imaging data was assessed. …”
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Vision-Based Pick and Place Control System for Industrial Robots Using an Eye-in-Hand Camera by van-Truong Nguyen, Phu-Tuan Nguyen, Shun-Feng Su, Phan Xuan Tan, Thanh-Lam Bui

“…To address this issue, our research focuses on utilizing a low-cost 2D camera combined with deep learning algorithms mounted on the end-effector of the robotic arm. …”
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Application of large language models in disease diagnosis and treatment by Xintian Yang, Tongxin Li, Qin Su, Yaling Liu, Chenxi Kang, Yong Lyu, Lina Zhao, Yongzhan Nie, Yanglin Pan, Yuanyuan Ji

“…Despite these promising developments, significant challenges persist regarding the use of LLMs in medicine, including concerns regarding algorithmic bias, the potential for hallucinations, and the need for rigorous clinical validation. …”
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A Novel Audio Copy Move Forgery Detection Method With Classification of Graph-Based Representations by Beste Ustubioglu, Gul Tahaoglu, Arda Ustubioglu, Guzin Ulutas, Muhammed Kilic

“…In this stage, the filtered audio is represented as a graph using the proposed spiral pattern information extraction method. Graph coloring algorithms are applied to convert the graph into a visual representation, which is then input into a specially designed Convolutional Neural Network (CNN) model for classification. …”
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Deep learning and hyperspectral features for seedling stage identification of barnyard grass in paddy field by Siqiao Tan, Qiang Xie, Wenshuai Zhu, Yangjun Deng, Lei Zhu, Xiaoqiao Yu, Zheming Yuan, Zheming Yuan, Yuan Chen, Yuan Chen

“…Notably, this surpasses the capabilities of other models that rely on amalgamations of machine learning algorithms and feature dimensionality reduction methods. …”
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