Prediction of ischemic stroke in patients with H-type hypertension based on biomarker by Ke Chen, Jianxun He, Lan Fu, Xiaohua Song, Ning Cao, Hui Yuan

“…Logistic regression, least absolute shrinkage and selection operator regression, and best subset selection analysis were used to assess the contribution of variables to ischemic stroke, and models were derived using four machine learning algorithms. Area Under Curve (AUC), calibration plot and decision-curve analysis respectively evaluated the discrimination and calibration of four models, then external validation and visualization of the best-performing model. …”
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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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Multi-View Collaborative Training and Self-Supervised Learning for Group Recommendation by Feng Wei, Shuyu Chen

“…One of the key challenges facing recommendation algorithms is data sparsity, a limitation that is even more severe in group recommendation than in traditional recommendation tasks. …”
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AI-assisted neurocognitive assessment protocol for older adults with psychiatric disorders by Diego D. Díaz-Guerra, Marena de la C. Hernández-Lugo, Yunier Broche-Pérez, Carlos Ramos-Galarza, Ernesto Iglesias-Serrano, Zoylen Fernández-Fleites

“…It employs machine learning algorithms to analyze test results, generating an individualized neurocognitive profile that highlights patterns and trends useful for clinical decision-making. …”
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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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Water vapor density field estimation using commercial microwave link attenuation combined with temperature measurements by Itay Bragin, Yoav Rubin, Pinhas Alpert, Jonatan Ostrometzky

“…A number of machine-learning based algorithms (e.g. support vector machine) for estimating water vapor density at a reference weather station using the received signal level values measured at a commercial microwave link has been proposed in the past, and also was expanded to include a combination of three commercial microwave links with temperature measurements to achieve a higher estimation accuracy (with respect to the root mean square error at a given location). …”
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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 >2 h were at a higher risk of early postoperative MACE compared to those with CPB duration ≤2 h. …”
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Precision Analysis of Multi-Parameter Multi-Epoch Emitter Localization Radar in Three-Satellite Formation by Yiming Lian, Yuxuan Wu, Yaowen Chen, Xian Liu, Liming Jiang

“…To address the issues of requiring numerous cooperative platforms and the poor accuracy of single-epoch solutions with single-parameter closed-form algorithms, this paper proposes a multi-parameter multi-epoch positioning method based on a three-satellite formation. …”
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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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