Optimizing Multivariable Logistic Regression for Identifying Perioperative Risk Factors for Deep Brain Stimulator Explantation: A Pilot Study by Peyton J. Murin, Anagha S. Prabhune, Yuri Chaves Martins

“…Recursive feature elimination with cross-validation (RFECV) optimized factor selection was used. A multivariate logistic regression model was trained and evaluated using precision, recall, F1-score, and area under the curve (AUC). …”
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Web-based machine learning application for interpretable prediction of prolonged length of stay after lumbar spinal stenosis surgery: a retrospective cohort study with explainable... by Paierhati Yasheng, Paierhati Yasheng, Alimujiang Yusufu, Yasenjiang Yimiti, Haopeng Luan, Cong Peng, Xinghua Song

“…The final optimal random forest (RF) model achieved an area under the curve (ROC) of 0.93 on the training set and 0.83 on the test set. …”
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Integration of metaheuristic based feature selection with ensemble representation learning models for privacy aware cyberattack detection in IoT environments by M. Karthikeyan, R. Brindha, Maria Manuel Vianny, V. Vaitheeshwaran, Mrinal Bachute, Sanket Mishra, Bibhuti Bhusan Dash

“…The data normalization stage initially applies Z-score normalization to convert input data into a beneficial format. The AMFS-ELPPCD model utilizes the adaptive Harris hawk optimization (AHHO) model for the feature process selection of the subset. …”
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Machine Learning for the estimation of foliar nitrogen content in pineapple crops using multispectral images and Internet of Things (IoT) platforms by Jorge Enrique Chaparro, José Edinson Aedo, Felipe Lumbreras Ruiz

“…These findings highlight the promising potential of developing machine learning models that integrate multisensor data fusion for various applications in agriculture.…”
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A fine-tuned convolutional neural network model for accurate Alzheimer’s disease classification by Muhammad Zahid Hussain, Tariq Shahzad, Shahid Mehmood, Kainat Akram, Muhammad Adnan Khan, Muhammad Usman Tariq, Arfan Ahmed

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Deep learning-based improved transformer model on android malware detection and classification in internet of vehicles by Naif Almakayeel

“…Then, the DLBITM-AMD approach utilizes the binary grey wolf optimization (BGWO) model to select optimum feature subsets. …”
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Leveraging explainable artificial intelligence with ensemble of deep learning model for dementia prediction to enhance clinical decision support systems by Mohamed Medani, Ghada Moh. Samir Elhessewi, Mohammed Alqahtani, Somia A. Asklany, Sulaiman Alamro, Da’ad Albalawneh, Menwa Alshammeri, Mohammed Assiri

“…Finally, the hyperparameter selection of ensemble models is accomplished by utilizing the gazelle optimization algorithm (GOA) technique. …”
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Sensitivity Analysis Based on E-TOPSIS Combined with MORIME-Based Multi-Objective Optimization for Sprayer Frame Design Optimization by Shaohao Zhou, Qi Chen, Lihua Zhang

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Prediction Method of Lithology Log Based on XGBoost Algorithm by CHU Qingjun, GE Yunlong, TONG Maosong, WANG Yan, AN Lyuxing, YU Chuanwu, JIA Xin

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A conceptual framework for integrating volunteers in emergency response planning and optimization assisted by decision support systems by Maziar Yazdani, Milad Haghani

“…We also explore and analyze existing methodologies for developing the analytical layers, the requirements of these models, and the current methodological gaps. The proposed framework establishes a clear roadmap for adopting emergency response approaches that are human-centric, but at the same time, effectively utilize advancements in modeling, optimization, machine learning, and data integration.…”
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Quality by Design and In Silico Approach in SNEDDS Development: A Comprehensive Formulation Framework by Sani Ega Priani, Taufik Muhammad Fakih, Gofarana Wilar, Anis Yohana Chaerunisaa, Iyan Sopyan

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MATHEMATICAL MODEL OF RESOURCE DISTRIBUTION OF THE COMPUTING CLUSTER OF CLOUD DATA CENTERS by V. P. Mochalov, G. I. Linets, N. Y. Bratchenko, I. S. Palkanov

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Lung Cancer Prediction Using an Enhanced Neutrosophic Set Combined with a Machine Learning Approach by Vakeel A. Khan, Asheesh Kumar Yadav, Mohammad Arshad, Nadeem Akhtar

“…Neutrosophic Set (NS) theory extends classical and fuzzy logic by introducing three independent membership components: truth, indeterminacy, and falsity, which enable more effective modeling of uncertainty in clinical datasets. The proposed ENS model enhances decision-making by optimizing feature selection and minimizing ambiguity in patient data representation. …”
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Feasibility Assessment of Novel Multi-Mode Camshaft Design Through Modal Analysis by Merve Üngör, Osman Taha Sen, Akif Yavuz, Cemal Baykara

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Potentials of the bio-inspired approach in the development of artificial intelligence systems (trends review) by A.R. Nurutdinov, R.Kh. Latypov

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Leveraging IGOOSE-XGBoost for the Early Detection of Subclinical Mastitis in Dairy Cows by Rui Guo, Yongqiang Dai

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YOLO-LSM: A Lightweight UAV Target Detection Algorithm Based on Shallow and Multiscale Information Learning by Chenxing Wu, Changlong Cai, Feng Xiao, Jiahao Wang, Yulin Guo, Longhui Ma

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Predicting Ocean Current Temperature Off the East Coast of America with XGBoost and Random Forest Algorithms Using Rstudio by Lulut Alfaris, Anas Noor Firdaus, Ukta Indra Nyuswantoro, Ruben Cornelius Siagian, Aldi Cahya Muhammad, Rohana Hassan, Rodulfo T. Aunzo, Jr., Reza Ariefka

“…This research investigates the comparative predictive efficacy of two leading machine learning methodologies, specifically the XGBoost and Random Forest models, in estimating ocean temperature dynamics in the TS Gulf Stream and Labrador Current regions along the east coast of North America. …”
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Analysis of service oriented network slicing at infrastructure layer in LoRa for IoT applications by Shilpi Verma, Sindhu Hak Gupta, Vipin Balyan

“…Additionally, different machine learning models have been employed to evaluate the effectiveness of the proposed slice classification strategy, confirming the reliability of communication-parameter-based slice allocation.…”
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Safe Switching Model-Free Value Iteration for General Nonlinear Systems by Timotei Lala

“…We propose an approach called Safe Switching Model-Free Value Iteration (SSMFVI), which guarantees both stability and safety of a system in closed loop with a controller optimized with Value Iteration in a model-free manner. …”
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