A Data-Driven Comparative Analysis of Machine-Learning Models for Familial Hypercholesterolemia Detection by Tomasz Kocejko

“…This study presents an assessment of familial hypercholesterolemia (FH) probability using different algorithms (CatBoost, XGBoost, Random Forest, SVM) and its ensembles, leveraging electronic health record data. …”
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Fault Diagnosis in a Four-Arm Delta Robot Based on Wavelet Scattering Networks and Artificial Intelligence Techniques by Claudio Urrea, Carlos Domínguez

“…This study compares time-domain signal features and wavelet scattering networks, applied by classification algorithms including wide neural networks (WNNs), efficient linear support vector machine (ELSVM), efficient logistic regression (ELR), and kernel naive Bayes (KNB). …”
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Water Quality Monitoring Using Landsat 8 OLI in Pleasant Bay, Massachusetts, USA by Haley E. Synan, Brian L. Howes, Sara Sampieri, Steven E. Lohrenz

“…Satellite-derived estimates of chlorophyll-a and Secchi depth were acquired using various algorithms including the “Case-2 Regional/Coast Color” (C2RCC), “Case-2 Extreme” (C2X), l2gen processor, and a random forest machine learning algorithm. …”
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Classification and Regression Trees analysis identifies patients at high risk for kidney function decline following hospitalization. by Weihao Wang, Wei Zhu, Janos Hajagos, Laura Fochtmann, Farrukh M Koraishy

“…Estimated glomerular filtration rate (eGFR) decline is associated with negative health outcomes, but the use of decision tree algorithms to predict eGFR decline is underreported. …”
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Paint shop vehicle sequencing based on quantum computing considering color changeover and painting quality by Jing Huang, Qing Chang, Hua-Tzu Fan

“…The problem is further converted to a quantum optimization problem and solved with Quantum Approximation Optimization Algorithm (QAOA). As a matter of fact, current quantum computers are still limited in accuracy and scalability. …”
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Long-Short Term Memory Networks and Synthetic Data for Heavy Vehicle Rollover Prevention by Guido Perboli, Antonio Tota, Filippo Velardocchia

“…Considering the same and other connected implications, the necessity for techniques able to estimate and predict overturning eventualities appears evident. …”
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Medication Adherence: does Patient Participation in Randomized Clinical Trials Affect on it? by N. O. Vasyukova, Yu. V. Lukina, N. P. Kutishenko, S. Yu. Martsevich, O. I. Zvonareva

“…., the absence of a “gold standard” for assessing adherence in clinical practice makes it difficult to predict and significantly improve it among patients. …”
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Revolutionizing Sperm Analysis with AI: A Review of Computer-Aided Sperm Analysis Systems by Francisco J. Baldán, Diego García-Gil, Carlos Fernandez-Basso

“…These advanced systems offer significant advantages, including enhanced objectivity, improved consistency over manual methods, and the ability to detect subtle predictive patterns not discernible by human observation. …”
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Tracking Secondary Raw Material Operational Framework—DataOps Case Study by Gabriel Pestana, Marisa Almeida, Nelson Martins

“…It enhances supply chain transparency through digital traceability, promotes predictive material sourcing, and streamlines logistics via algorithmic optimization. …”
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An exploration of machine learning approaches for early Autism Spectrum Disorder detection by Nawshin Haque, Tania Islam, Md Erfan

“…This study explores the application of Logistic Regression, Support Vector Classifier, K-Nearest Neighbour, Decision Tree, and Random Forest for predicting Autism in children and toddlers by leveraging advancements in machine learning. …”
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The Potential of Unsupervised Induction of Harmonic Syntax for Jazz by Ruben Cartuyvels, John Koslovsky, Marie-Francine Moens

“…Hierarchical structures describing a syntax of harmony have long been studied and proposed by music theorists, but algorithms that model these structures either require costly expert annotations for training or are based on music theorists' predispositions about harmonic syntax. …”
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Smart Thermostat Development and Validation on an Environmental Chamber Using Surrogate Modelling by Leonidas Zouloumis, Nikolaos Ploskas, Nikolaos Taousanidis, Giorgos Panaras

“…Although dynamic simulation tools and decision-making algorithms are core components of energy management methodologies, they are often accompanied by excessive computational cost. …”
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A Review of Embodied Grasping by Jianghao Sun, Pengjun Mao, Lingju Kong, Jun Wang

“…Then, the embodied algorithms are introduced, starting from pre-trained models, with three main research goals: (1) embodied perception, using data captured by visual sensors to perform point cloud extraction or 3D reconstruction, combined with pre-trained models, to understand the target object and external environment and directly predict the execution of actions; (2) embodied strategy: In imitation learning, the pre-trained model is used to enhance data or as a feature extractor to enhance the generalization ability of the model. …”
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Artificial Intelligence in Glioblastoma—Transforming Diagnosis and Treatment by Alen Rončević, Nenad Koruga, Anamarija Soldo Koruga, Robert Rončević

“…They can also enhance prognostication by predicting survival, recurrence, and treatment responses, helping clinicians to make more informed decisions. …”
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Modern Approach in Pattern Recognition Using Circular Fermatean Fuzzy Similarity Measure for Decision Making with Practical Applications by Revathy Aruchsamy, Inthumathi Velusamy, Prasantha Bharathi Dhandapani, Suleman Nasiru, Christophe Chesneau

“…Machine learning algorithm utilizes pattern recognition as an instrument for identifying patterns and also similarity measure (SM) is a beneficial pattern recognition tool used to classify items, discover variations, and make future predictions for decision making. …”
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Global miniaturization of broadband antennas by prescreening and machine learning by Slawomir Koziel, Anna Pietrenko-Dabrowska, Ubaid Ullah

“…Our technique includes parameter space pre-screening and the iterative refinement of kriging surrogate models using the predicted merit function minimization as an infill criterion. …”
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Comprehensive multi-omics analysis of histone acetylation modulators identifies ASH1L as a novel aggressive marker for osteosarcoma by Chenlie Ni, Qiwen Sun, Haibo Yin

“…The effectiveness of HAMRPs in predicting the immune landscape of osteosarcoma was confirmed using CIBERSORT, ssGSEA, and ESTIMATE algorithms. …”
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ULOTrack: Underwater Long-Term Object Tracker for Marine Organism Capture by Ju He, Yang Yu, Hongyu Wei, Hu Xu

“…Therefore, existing tracking algorithms face difficulty in direct application to underwater object tracking. …”
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A comprehensive review of flood damage in mountainous regions: challenges, solutions, and advanced management technologies by Mohammad Roohi, Jila Dehghani, Maryam Irani, Paramiss Mina

“…Modern technologies, early warning systems, predictive models, and international collaboration are key to reducing flood losses and informing sustainable flood management.…”
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Climate risk and low-carbon policies: implications for sports economics and global events by Siyu Fu, Chen Kong

“…ICSF, on the other hand, leverages game theory and optimization algorithms to enhance decision-making in areas such as resource allocation, salary cap management, and sustainability-oriented strategic planning.ResultsEmpirical results from multiple datasets and experiments confirm that the integration of climate risk and low-carbon policy variables significantly improves the predictive accuracy and resilience of economic planning in the sports sector.DiscussionThis research provides theoretical advancements and practical insights for policymakers, sports managers, and investors seeking to navigate the complex interplay between sustainability and profitability in a rapidly changing global environment.…”
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