VAS value set still has its own application value compare with TTO value set of EQ-5D-3L in Chinese population by Lin Zhuo, Siyuan Gao, Rui Jin, Lang Zhuo, Xiuying Wang

“…Five categories of indices, including quality of original data, distribution of rescaled values, goodness of fit of models, distribution of predicted values, and dimensions order were adopted to compare between Chinese VAS and TTO value sets. …”
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Evaluating soil erosion zones in the Kangsabati River basin using a stacking framework and SHAP model: a comparative study of machine learning approaches by Javed Mallick, Saeed Alqadhi, Swapan Talukdar, Md Nawaj Sarif, Tania Nasrin, Hazem Ghassan Abdo

“…Abstract Soil erosion is a major concern in the Kangsabati River basin, necessitating a comprehensive scientific approach for effective soil erosion management. This study aimed to predict soil erosion susceptibility zones in the basin using integrated soil erosion and deep learning (DL) based stacking framework. …”
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Uncertainty analysis of clinically relevant distances derived using photogrammetric intersection for the assessment of motor-speech-control in children by L. Boyle, P. Helmholz, R. Ward, R. Palmer, D. Lichti

“…In contrast, photogrammetry can predict facial inter-landmark distances and their uncertainties through intersection and variance propagation. …”
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Emulating real-world GLP-1 efficacy in type 2 diabetes through causal learning and virtual patients. by Calum Robert MacLellan, Hristo Petkov, Conor McKeag, Feng Dong, David John Lowe, Roma Maguire, Sotiris Moschoyiannis, Jo Armes, Simon Skene, Alastair Finlinson, Christopher Sainsbury

“…We validate the virtual trials by comparing the predicted impact of glucagon-like peptide-1 (GLP-1) agonists on HbA1c in type-2 diabetes (T2DM) with its true efficacy established in the LEAD-5 trial. …”
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An Intelligent Crow Search Optimization and Bi-GRU for Forest Fire Detection System Using Internet of Things by Syed Abdul Moeed, Bellam Surendra Babu, M. Sreevani, B. V. Devendra Rao, R. Raja Kumar and Gouse Baig Mohammed

“…This neural network architecture is capable of processing sequential data from multiple directions, enhancing the system’s ability to predict the spread and intensity of fires. Crow Search Optimization (CSO) and fractional calculus are used to create an optimal solution in the proposed crow search fractional calculus optimization (CSFCO) algorithm for deep learning. …”
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Modelos univariados de séries temporais para previsão das temperaturas médias mensais de Erechim, RS Univariate time series methods for forecasting the monthly mean air temperature... by Leonardo Chechi, Fábio M. Bayer

“…In the class of ARIMA models using criteria information, SARIMA type models that consider the seasonal characteristics of air temperature were selected, whereas for exponential smoothing models Holt-Winters additive algorithm were used. Smoothing constants are determined to minimize the mean square error between observed and predicted values. …”
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Effect of Molarity of Sodium Hydroxide on the Strength Behavior of Fiber-Reinforced Geopolymer Concrete Exposed to Elevated Temperature by Abbasali Saffar, Mohammad Ehsanifar, Seyed Mohammad Mirhoseini, Mohammad Javad Taheri Amiri

“…Beside, post-fire strength of FRGPC was predicted using artificial neural network (ANN) and support vector machines (SVM) with the integration of water cycle algorithm (WCA). …”
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Race course characteristics are the most important predictors in 48 h ultramarathon running by Beat Knechtle, David Valero, Elias Villiger, Katja Weiss, Pantelis T. Nikolaidis, Lorin Braschler, Rodrigo Luiz Vancini, Marilia Santos Andrade, Ivan Cuk, Thomas Rosemann, Mabliny Thuany

“…A machine learning (ML) model based on the XG Boost algorithm was built to predict running speed from the athlete´s age, gender, country of origin, where the race occurs and race course characteristic such as elevation (flat or hilly) and surface (asphalt, cement, granite, grass, gravel, sand, track, or trail). …”
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MAP17 is a Novel NASH Progression Biomarker Associated with Macrophage Infiltration, Immunotherapy Response, and Oxidative Stress by Huang Z, Chen J, Liu S, Xiang X, Long Y, Tan P, Fu W

“…Our further analyses included differential expression evaluation, protein-protein interaction (PPI) network analysis, and Venn diagram analysis to discover novel targets. The CIBERSORT algorithm assessed the correlation between MAP17 and immune cell infiltration within the tumor microenvironment (TME), while the TIDE algorithm predicted responses to immunotherapy. …”
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Theoretical investigation of the free fall of a spherical particle in a viscous fluid using continuous piecewise linearization method by Akuro Big-Alabo, Joseph Chukwuka Ofodu

“…The CPLM algorithm was shown to predict published experimental results accurately and compared very well with numerical solutions and existing analytical solutions. …”
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A Multi-Input Neural Network Model for Accurate MicroRNA Target Site Detection by Mohammad Mohebbi, Amirhossein Manzourolajdad, Ethan Bennett, Phillip Williams

“…These images are processed in parallel by the MINN algorithm, allowing it to learn a comprehensive and precise representation of the underlying biological mechanisms. (3) Results: Our method, on an experimentally validated test set, detects target sites with an AUPRC of 0.9373, Precision of 0.8725, and Recall of 0.8703 and outperforms several commonly used computational methods of microRNA target-site predictions. (4) Conclusions: Incorporating diverse biologically explainable features, such as duplex structure, substructures, their MFEs, and binding probabilities, enables our model to perform well on experimentally validated test data. …”
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Radiographic Measurements and Diagnosis of Hip Dysplasia in Infants Using Computer Vision and a Rule-Based System by Ernesto Pérez Pérez, Roberto Díaz Amador, Karina Leonor Fernández Sánchez, José Julio Requeiro Molina, José Julio Requeiro Morejón

“…<strong><br />Conclusion</strong>: there was a high coincidence between the measures calculated by the algorithm and those calculated manually. The correspondence between the diagnosis predicted by the system and that issued by specialist doctors was also high.…”
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Artificial Intelligence for Fault Detection of Automotive Electric Motors by Federico Soresini, Dario Barri, Ivan Cazzaniga, Federico Maria Ballo, Gianpiero Mastinu, Massimiliano Gobbi

“…This study focuses on durability testing of Permanent Magnet Synchronous Motors for automotive applications, using Autoencoders (AEs) to predict and prevent failures. This AI-based fault detection strategy employs acceleration signals coming from electric motors tested under challenging conditions with significant variations in torque and speed. …”
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Evolutionary Computation for Modelling Social Traits in Realistic Looking Synthetic Faces by Felix Fuentes-Hurtado, Jose A. Diego-Mas, Valery Naranjo, Mariano Alcañiz

“…A model of how observers will perceive a face based on its features’ appearances and relative positions was developed and used as the fitness function of the algorithm. The model is able to predict 15 facial social traits related to aesthetic, moods, and personality. …”
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Short‐term electric power and energy balance optimization scheduling based on low‐carbon bilateral demand response mechanism from multiple perspectives by Juan Li, Yonggang Li, Huazhi Liu

“…The enhanced decision tree classifier (EDTC) algorithm is used to predict the electricity consumption behavior of transferable load (TL) users, and an improved particle swarm optimization (PSO) algorithm with “ε‐greedy” strategy is proposed to solve this model. …”
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Task allocation and path planning for multi-robot systems in intelligent warehousing by CHU Jing, TIAN Yiqiu, YUE Qi, HUANG Yong

“…The study proposes a warehouse task allocation strategy that incorporates traffic flow impact factors into the auction algorithm, optimizing task allocation by predicting robot density in various areas of the environment. …”
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Deep learning for automated segmentation of radiation-induced changes in cerebral arteriovenous malformations following radiosurgery by Hsing-Hao Ho, Huai-Che Yang, Wen-Xiang Yang, Cheng-Chia Lee, Hsiu-Mei Wu, I-Chun Lai, Ching-Jen Chen, Syu-Jyun Peng

“…The algorithm could be used to predict the course of RICs and facilitate clinical management. …”
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Driving Pattern Analysis, Gear Shift Classification, and Fuel Efficiency in Light-Duty Vehicles: A Machine Learning Approach Using GPS and OBD II PID Signals by Juan José Molina-Campoverde, Juan Zurita-Jara, Paúl Molina-Campoverde

“…A multiple linear regression model was developed to estimate instantaneous fuel consumption (in L/100 km) using the gear predicted by the KNN algorithm and other relevant variables. …”
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Assessment model of ozone pollution based on SHAP-IPSO-CNN and its application by Xiaolei Zhou, Xingyue Wang, Ruifeng Guo

“…Firstly, an atmospheric dispersion model is utilized to predict the distribution concentration of VOCs emitted by enterprises in the park at the target monitoring stations based on the ozone generation mechanism. …”
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Leveraging ensemble learning-based stock preselection with multiobjective investment optimization for stepwise decision-supported portfolio management by Jui-Sheng Chou, Tran-Bao-Quyen Pham

“…In the first phase, the FBI-XGB model predicts company profitability, selecting candidates with higher expected returns. …”
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