Enhancing multiclass brain tumor diagnosis using SVM and innovative feature extraction techniques by Mustafa Basthikodi, M. Chaithrashree, B. M. Ahamed Shafeeq, Ananth Prabhu Gurpur

“…This research addresses the challenge of multiclass categorization by employing Support Vector Machine (SVM) as the core classification algorithm and analyzing its performance in conjunction with feature extraction techniques such as Histogram of Oriented Gradients (HOG) and Local Binary Pattern (LBP), as well as the dimensionality reduction technique, Principal Component Analysis (PCA). …”
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Soil liquefaction assessment using machine learning by Gamze Maden Muftuoglu, Kaveh Dehghanian

“…Compared to other approaches, the study assesses how well these algorithms predict soil liquefaction potential. Early findings show that the algorithms perform well, demonstrating their capacity to identify non-linear connections and improve prediction accuracy. …”
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Analysis of multiple faults in induction motor using machine learning techniques by Puja Pohakar, Ravi Gandhi, Surender Hans, Gulshan Sharma, Pitshou N. Bokoro

“…Due to their limits, machine learning algorithms outperform traditional methods in real-time fault diagnosis, predictive maintenance, and multi-fault categorization. …”
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Estimation single output with a hybrid of ANFIS and MOPSO_HS by Aref Yelghi

“…In the field of soft computing, the Adaptive Neuro-Fuzzy Inference System (ANFIS) has been more well-liked in recent years for its predictive capabilities. Appropriate ANFIS parameter adjusting is critical, which creates a gap in its predictive integration with traditional optimization techniques. …”
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Improvement of an Edge-IoT Architecture Driven by Artificial Intelligence for Smart-Health Chronic Disease Management by William Alberto Cruz Castañeda, Pedro Bertemes Filho

“…The study also establishes a baseline of twelve regression algorithms to assess the non-invasive glucose prediction performance regarding the mean squared error, root mean squared error, and r-squared score, and the catboost regressor outperforms the other models with 218.91 and 782.30 in MSE, 14.80 and 27.97 in RMSE, and 0.81 and 0.31 in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula>, respectively, on training and test sets. …”
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Soil Parameter Inversion in Dredger Fill Strata Using GWO-MLSSVR for Deep Foundation Pit Engineering by Changrui Chen, Sifan Li, Jinbi Ye, Fangjian Chen, Yibin Wu, Jin Yu, Yanyan Cai, Jinna Lin, Xianqi Zhou

“…Compared to traditional inversion methods and MLSSVR models optimized by other algorithms, this approach significantly reduces prediction errors. …”
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Machine learning-based construction of a programmed cell death-related model reveals prognosis and immune infiltration in pancreatic adenocarcinoma patients by Bing Wang, Zhida Long, Xun Zou, Zhengang Sun, Yuanchu Xiao

“…The model was validated to have robust predictive performance. Risk scores were significantly correlated with clinical features, immune microenvironment characteristics, and chemotherapeutic sensitivity. …”
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Hybrid Intelligence approach to study post-processing impact on the mechanical performance of notched additively manufactured AlSi10Mg by Erfan Maleki, Sara Bagherifard, Okan Unal, Mario Guagliano

“…In parallel, Artificial Intelligence (AI), utilizing advanced machine learning (ML) algorithms, performed tasks related to prediction, sensitivity analysis, and parametric analysis. …”
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A Review of Computer Vision Technology for Football Videos by Fucheng Zheng, Duaa Zuhair Al-Hamid, Peter Han Joo Chong, Cheng Yang, Xue Jun Li

“…In the era of digital advancement, the integration of Deep Learning (DL) algorithms is revolutionizing performance monitoring in football. …”
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Application of selective ensemble learning soft sensor modeling based on GPR in the solar thermal power collection system by Yalu Sun, Kun Ding, Changhai Yang, Zhuxiu Wang

“…Therefore, a novel predictive control method for the outlet temperature of the collector system is proposed based on the Gaussian process regression selective ensemble learning soft sensing model (SESMGPR). …”
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The clinical performance of an office-based risk scoring system for fatal cardiovascular diseases in North-East of Iran. by Sadaf G Sepanlou, Reza Malekzadeh, Hossein Poustchi, Maryam Sharafkhah, Saeed Ghodsi, Fatemeh Malekzadeh, Arash Etemadi, Akram Pourshams, Paul D Pharoah, Christian C Abnet, Paul Brennan, Paolo Boffetta, Sanford M Dawsey, Farin Kamangar

“…Cardiovascular risk functions for prediction of 10-year risk of fatal CVDs were developed.…”
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A review on artificial intelligence thermal fluids and the integration of energy conservation with blockchain technology by Abdullah Ayub Khan, Asif Ali Laghari, Syed Azeem Inam, Sajid Ullah, Laila Nadeem

“…A cost-effective energy management environment that supports international energy conservation initiatives is created by combining the predictive power of AI with the security features of blockchain technology. …”
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Estimating Leaf Chlorophyll Fluorescence Parameters Using Partial Least Squares Regression with Fractional-Order Derivative Spectra and Effective Feature Selection by Jie Zhuang, Quan Wang

“…We developed a data-driven partial least squares regression (PLSR) model by integrating fractional-order derivative (FOD) spectral transformation with multiple feature selection methods to predict ChlF parameters. The results demonstrated that FOD spectra effectively improved prediction accuracy compared to conventional PLSR attempts. …”
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Clinical application and immune infiltration landscape of stemness‐related genes in heart failure by Wenting Yan, Yanling Li, Gang Wang, Yuan Huang, Ping Xie

“…Feature selection was performed using two machine learning algorithms. Nomogram models were then constructed to predict HF risk based on the selected key genes. …”
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AI-Driven Innovation in Skin Kinetics for Transdermal Drug Delivery: Overcoming Barriers and Enhancing Precision by Nubul Albayati, Sesha Rajeswari Talluri, Nirali Dholaria, Bozena Michniak-Kohn

“…Advances in artificial intelligence (AI) address these challenges through predictive modeling and personalized medicine approaches. …”
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A Review of Recent Advances in Roll Stability Control in On-Road and Off-Road Vehicles by Jie Chen, Ruochen Wang, Wei Liu, Dong Sun, Yu Jiang, Renkai Ding

“…Furthermore, the integration of machine learning and advanced predictive algorithms promises to enhance the intelligence and versatility of roll stability control systems.…”
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The Impact of Integrating Variable Renewable Energy Sources into Grid-Connected Power Systems: Challenges, Mitigation Strategies, and Prospects by Emmanuel Ejuh Che, Kang Roland Abeng, Chu Donatus Iweh, George J. Tsekouras, Armand Fopah-Lele

“…Many research efforts in using prediction models have developed real-time monitoring of variability and machine learning predictive algorithms in contrast to the conventional methods of studying variability. …”
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Application of Machine Tool Thermal Error Compensation in Digital Twin-based System by MA Chi, LI Minging, LIU Jialan, HE Jialong, HUA Chunlei, WANG Liang

“…Moreover, a novel collinearity exclusion-based thermal error method is proposed in this work based on the modified tolerance value. A novel prediction model utilizing a strong-convergence chimp optimization algorithm combined with a minimal gated unit-attention mechanism is proposed to characterize the dependence of the current thermal error on the historical thermal informant data, forming strong-convergence chimp optimization algorithm-minimal gated unit-attention ( SC-ChOA-MGU-A) model,ensuring data integrity. …”
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Combined Analysis of Transcriptome and Mendelian Randomization Reveals AKT1 and PPARG as Biomarkers Related to Glucose Metabolism in Sepsis by Ma J, Li W, Ma Q, Ding L, Wang Z, Wang R, Huang Y, Ma G, Gao J

“…Jie Ma,1,2,&amp;ast; Wendi Li,3 Qianqian Ma,1 Liying Ding,4 Zhaoyun Wang,1 Rong Wang,1 Yanan Huang,1 Gang Ma,2,&amp;ast; Jun Gao1,&amp;ast; 1Department of Anesthesia and Perioperative Medicine, First People’s Hospital of Yinchuan, The Second Clinical Medical College of Ningxia Medical University, Yinchuan, Ningxia, 750001, People’s Republic of China; 2Department of Anesthesia and Perioperative Medicine, General Hospital of Ningxia Medical University, The First Clinical Medical College of Ningxia Medical University, Yinchuan, Ningxia, 750004, People’s Republic of China; 3Department of Child Rehabilitation Education, Ningxia Rehabilitation Center for the Disabled, Yinchuan, Ningxia, 750002, People’s Republic of China; 4Department of Gynecology, Gynecology Clinic of Li Ying, Wuzhong, Ningxia, 751100, People’s Republic of China&amp;ast;These authors contributed equally to this workCorrespondence: Gang Ma, Department of Anesthesia and Perioperative Medicine, General Hospital of Ningxia Medical University, The First Clinical Medical College of Ningxia Medical University, Yinchuan, Ningxia, 750004, People’s Republic of China, Email magang2671@163.com Jun Gao, Department of Anesthesia and Perioperative Medicine, First People’s Hospital of Yinchuan, The Second Clinical Medical College of Ningxia Medical University, Yinchuan, Ningxia, 750001, People’s Republic of China, Email gaojun1605@sina.comIntroduction: This study aimed to identify diagnostic and therapeutic biomarkers related to glucose metabolism in sepsis, as hyperglycemia and blood glucose fluctuations influence sepsis progression.Methods: Datasets from public databases were analyzed using various methods, including differential expression analysis, PPI network screening, machine learning algorithms and Mendelian randomization. …”
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A Combined Deep Learning Method with Attention-Based LSTM Model for Short-Term Traffic Speed Forecasting by Pan Wu, Zilin Huang, Yuzhuang Pian, Lunhui Xu, Jinlong Li, Kaixun Chen

“…Results show that the proposed method outperforms other deep learning algorithms (such as recurrent neural network (RNN) and convolutional neural network (CNN)) in terms of both calculating efficiency and prediction accuracy. …”
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