A Combined Approach Using T2*-Weighted Dynamic Susceptibility Contrast MRI Perfusion Parameters and Radiomics to Differentiate Between Radionecrosis and Glioma Progression: A Proof... by José Pablo Martínez Barbero, Francisco Javier Pérez García, David López Cornejo, Marta García Cerezo, Paula María Jiménez Gutiérrez, Luis Balderas, Miguel Lastra, Antonio Arauzo-Azofra, José M. Benítez, Antonio Jesús Láinez Ramos-Bossini

“…This study aimed to develop and evaluate a machine learning model that integrates radiomics features and T2*-weighted Dynamic Susceptibility Contrast MRI perfusion (DSC MRI) parameters to improve diagnostic accuracy in distinguishing these entities. …”
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Machine Learning-Driven Optimization of Machining Parameters Optimization for Cutting Forces and Surface Roughness in Micro-Milling of AlSi10Mg Produced by Powder Bed Fusion Additi... by Zihni Alp Cevik, Koray Ozsoy, Ali Ercetin, Gencay Sariisik

“…This study focuses on optimizing machining parameters in the micro-milling of AlSi10Mg aluminum alloy produced via the powder bed fusion additive manufacturing process. …”
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Enhanced Prediction and Evaluation of Hydraulic Concrete Compressive Strength Using Multiple Soft Computing and Metaheuristic Optimization Algorithms by Tianyu Li, Xiamin Hu, Tao Li, Jie Liao, Lidan Mei, Huiwen Tian, Jinlong Gu

“…Concrete is the material of choice for constructing hydraulic structures in water-related buildings, and its mechanical properties are crucial for evaluating the structural damage state. Machine learning models have proven effective in predicting these properties. …”
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Evaluation of Organic (Cow Dung) and Inorganic (NPK) Fertilizers for the Increase of Yields in Cabbages (Brassica Oleracea Var.Capitata). by Nabireeba, Cosma

“…The research study was carried out to evaluate the effect of organic and inorganic fertilizers on the increase of yields in cabbages (brassica oleracea var.capitata). …”
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Low-cost fabrication and comparative evaluation of machine learning algorithms for flexible PDMS-based hexagonal patch antenna by Srivatsan Sarvesan, Mettu Goutham Reddy, S. S. Karthikeyan, Praveen K. Sekhar

“…To accelerate the design process and determine the most effective model for predicting optimal geometrical parameters that yield improved impedance matching at the target frequency, four supervised machine learning algorithms including Random Forest, XGBoost, CatBoost and LightGBM were evaluated and compared. …”
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Evaluation of the predictors of tooth loss using artificial intelligence-based machine learning approach: A retrospective study by Amit Rajabhau Pawar, Sankari Malaiappan, Pradeep Kumar Yadalam, P R Ganesh

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Predictive modelling of hexagonal boron nitride nanosheets yield through machine and deep learning: An ultrasonic exfoliation parametric evaluation by Jerrin Joy Varughese, Sreekanth M․S․

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Evaluation Modeling of Electric Bus Interior Sound Quality Based on Two Improved XGBoost Algorithms Using GS and PSO by Enlai ZHANG, Yi CHEN, Liang SU, Ruoyu ZHONGLIAN, Xianyi CHEN, Shangfeng JIANG

“…Aiming at the practical application requirements of high-precision modeling of acoustic comfort in vehicles, this paper presented two improved extreme gradient boosting (XGBoost) algorithms based on grid search (GS) method and particle swarm optimization (PSO), respectively, with objective parameters and acoustic comfort as input and output variables, and established three regression models of standard XGBoost, GS-XGBoost, and PSO-XGBoost through data training. …”
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Evaluating oxide nanoparticle exsolution on A-site deficient PrBaCo2O6-δ electrodes by Alfonso J Carrillo, María Balaguer, Cecilia Solís, Andrés López-García, Sylvio Haas, María Fabuel, Blanca Delgado-Galicia, Isabelle Rodriguez, Einar Vøllestad, Sebastian Wachowski, Ragnar Strandbakke, Truls Norby, Jose M Serra

“…Oxide exsolution in PrBa _1− _x Co _2 O _6− _δ aimed at boosting the electrocatalytic activity and was evaluated by varying intrinsic materials-related properties, viz. …”
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The Effect of Low Temperature and Low Illumination Intensity on the Photosynthetic Characteristics and Antioxidant Enzyme Activity in the Strawberry by Xinlong Hu, Chao Xu, Huihui Tao, Siyu Wang, Meng Zhang, Qian Chen, Huanxin Zhang, Guoquan Li, Chengpu Yan

“…Importantly, the previously mentioned photosynthetic physiological parameters showed notable changes under the combined stress conditions. …”
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Development and Validation of a Prediction Model Using Sella Magnetic Resonance Imaging–Based Radiomics and Clinical Parameters for the Diagnosis of Growth Hormone Deficiency and I... by Kyungchul Song, Taehoon Ko, Hyun Wook Chae, Jun Suk Oh, Ho-Seong Kim, Hyun Joo Shin, Jeong-Ho Kim, Ji-Hoon Na, Chae Jung Park, Beomseok Sohn

“…The extreme gradient boosting algorithm was used to train the prediction models. …”
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An interpretable and stacking ensemble model for predicting heat and mass transfer of desiccant wheel by Mengyang Li, Liu Chen

“…In addition, the contribution of each input feature and the decision-making process of the model are analyzed using the Shapley additive explanations. To evaluate the model, 13,095 data sets of desiccant wheel operation data were collected. …”
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Advancing Geotechnical Evaluation of Wellbores: A Robust and Precise Model for Predicting Uniaxial Compressive Strength (UCS) of Rocks in Oil and Gas Wells by Mohammadali Ahmadi

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Performance optimization of photovoltaic induction motor pumping system with Sliding mode control by Lehssen Mohamed Yahya Sidi, Ahmed Essadki, Hbib Mahfoudh, Cherkaoui Mohamed

“…The configuration utilizes a solar PV source with boost converter implementing, a two-level inverter for AC conversion and an induction motor mechanically linked to a centrifugal pump. …”
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Optimizing Nutrition Protocols for Improved Rice Yield, Quality, and Nitrogen Use Efficiency in Coastal Saline Soils by Xiang Zhang, Xiaoyu Geng, Yang Liu, Lulu Wang, Jizou Zhu, Weiyi Ma, Xiaozhou Sheng, Lei Shi, Yinglong Chen, Pinglei Gao, Huanhe Wei, Qigen Dai

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Application of a Hybrid Model for Data Analysis in Hydroponic Systems by Kuanysh Bakirov, Jamalbek Tussupov, Akhmet Tussupov, Ibraheem Shayea, Aruzhan Shoman

“…Experimental evaluation demonstrated superior predictive performance by using XGBoost, achieving an accuracy and F1-score of 97.88%, ROC-AUC of 99.99%, and computational efficiency (training completed in 2.3 s), outperforming RandomForest and GradientBoosting algorithms. …”
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Evaluating the Effects of Mitigating Urban Heat Islands of Green Infrastructure on Increasing the Productivity of Light and Heavy Work (Case Study: Tabriz Metropolitan) by Mahdi Herischian, Hassan Mahmoudzadeh, Rasoul Ghorbani

“…In this model, vegetation cover served as a key parameter for estimating heat island mitigation. Ultimately, the model assessed the service value of heat island mitigation using two evaluation methods: energy consumption (potential energy reduction) and labor productivity (light and heavy work). …”
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Evaluating the Cosmetic Efficacy of Topical <i>Micrococcus luteus</i> Q24 Probiotic Balm: A Pilot Study in Healthy Adults by Abigail L. Voss, Stephanie A. Mattison, Sonali S. Sali, John D. F. Hale, Rohit Jain

“…Firstly, the compatibility and growth-promoting effects of prebiotics and functional actives on <i>M. luteus</i> Q24 were evaluated, identifying oil-based actives, including vitamin E and pomegranate seed oil, that significantly boosted bacterial growth compared to oatmeal, the sole effective prebiotic tested. …”
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Evaluation of Prediction Models for the Capping and Breaking Force of Tablets Using Machine Learning Tools in Wet Granulation Commercial-Scale Pharmaceutical Manufacturing by Sun Ho Kim, Su Hyeon Han, Dong-Wan Seo, Myung Joo Kang

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Application of Compost as an Organic Amendment for Enhancing Soil Quality and Sweet Basil (<i>Ocimum basilicum</i> L.) Growth: Agronomic and Ecotoxicological Evaluation by Majda Oueld Lhaj, Rachid Moussadek, Latifa Mouhir, Hatim Sanad, Khadija Manhou, Oumaima Iben Halima, Hasna Yachou, Abdelmjid Zouahri, Meriem Mdarhri Alaoui

“…Using a randomized complete block design with six compost application rates, this study evaluated the physicochemical, biochemical, and agronomic responses of both soil and plants. …”
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