Demystifying multiple sclerosis diagnosis using interpretable and understandable artificial intelligence by Chadaga Krishnaraj, Khanna Varada Vivek, Prabhu Srikanth, Sampathila Niranjana, Chadaga Rajagopala, Palkar Anisha

“…However, symptoms can be managed, and treatments can be provided if the disease is diagnosed early. Hence, supervised machine learning (ML) algorithms and several hyperparameter tuning techniques, including Bayesian optimization, have been utilized in this study to predict MS in patients. …”
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A Robust Regression-Based Modeling to Predict Antiplasmodial Activity of Thiazolyl–Pyrimidine Hybrid Derivatives against <i>Plasmodium falciparum</i> by Kevin S. Umoette, Charles O. Nnadi, Wilfred O. Obonga

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Progress and current trends in prediction models for the occurrence and prognosis of cancer and cancer-related complications: a bibliometric and visualization analysis by Siyu Li, Wenrui Li, Xiaoxiao Wang, Wanyi Chen

“…Systematic reviews of cancer-related predictive models, which could help clinicians select the optimal model for specific clinical conditions may emerge as potential research directions in this field.…”
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Continuous prediction of human knee joint angle using a sparrow search algorithm optimized random forest model based on sEMG signals by Liuyi Ling, Zhu Lin, Bin Feng, Liyu Wei, Li Jin, Yiwen Wang

“…Continuous prediction of human joint angles is crucial for enhancing the performance of man-machine cooperative control. This study proposed a random forest (RF) model optimized by the sparrow search algorithm (SSA) for achieving continuous motion prediction of the lower limb knee joint based on surface electromyography(sEMG) under various motion modes. …”
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Half-hourly electricity price prediction model with explainable-decomposition hybrid deep learning approach by Sujan Ghimire, Ravinesh C. Deo, Konstantin Hopf, Hangyue Liu, David Casillas-Pérez, Andreas Helwig, Salvin S. Prasad, Jorge Pérez-Aracil, Prabal Datta Barua, Sancho Salcedo-Sanz

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Machine learning for orbit steering in the presence of nonlinearities by Simona Bettoni, Jonas Kallestrup, Güney Erin Tekin, Michael Böge, Romana Boiger

“…A possible limitation of ML for this application is the potential change in the dimensionality of the ML model after optimization, which could affect performance. …”
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Particle swarm optimization-based NLP methods for optimizing automatic document classification and retrieval. by Bowen Zeng, Xianhe Shang, Rong Lu, Yugui Zhang

“…To overcome these limitations, we propose the PBX model, which integrates both deep learning and traditional machine learning techniques. …”
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Solar FaultNet: Advanced Fault Detection and Classification in Solar PV Systems Using SwinProba‐GeNet and BaBa Optimizer Models by Praveen Kumar Balachandran, Muhammad Ammirrul Atiqi Mohd Zainuri, Faisal Alsaif

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Adaptive neuro-fuzzy inference system optimization of natural rubber latex modified concrete’s mechanical Properties by Efiok Etim Nyah, David Ogbonna Onwuka, Joan Ijeoma Arimanwa, George Uwadiegwu Alaneme, G. Nakkeeran, Ulari Sylvia Onwuka, Chinenye Elizabeth Okere

“…This study highlights the potential of NRLMC as a sustainable, high-performance material and demonstrates the efficacy of intelligent modeling for material optimization. By integrating machine learning with experimental data, this research advances the development of environmentally friendly and durable concrete, offering a scalable solution for future construction practices.…”
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Quantum AI: A Cognitive Machine Learning Technique based on Nurturing Food Security Sustainability Predictive Analysis for Life Science - Bioengineering in Healthcare by Senthil G.A., Monica K.M., Prabha R., Prinslin L., Elavarasi R.

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Use Cases of Machine Learning in Queueing Theory Based on a <i>GI</i>/<i>G</i>/<i>K</i> System by Dmitry Efrosinin, Vladimir Vishnevsky, Natalia Stepanova, Janos Sztrik

“…Machine learning (ML) in queueing theory combines the predictive and optimization capabilities of ML with the analytical frameworks of queueing models to improve performance in systems such as telecommunications, manufacturing, and service industries. …”
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REVIEW OF FEATURE SELECTION METHODS USING OPTIMIZATION ALGORITHM (Review paper for optimization algorithm) by Zana O. Hamad

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Research of the Parameter Comprehensive Optimization of Excavator Working Device based on the Hybrid Optimization Algorithm by Zhang Xian, Liu Baixi, Qu Tao

“…In order to optimize the performance of excavator in the specific region,The mathematical model of optimization design is obtained constrained by operating performance and mechanical property of the working device. …”
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Efficient resource allocation in cloud environment using SHO-ANN-based hybrid approach by Sanjeev Sharma, Pradeep Singh Rawat

“…The existing static, dynamic, and Meta-Heuristic approaches provide the solution to the virtual machine allocation problem. These techniques stuck with the local optimal solution. …”
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Optimization of process parameters in 3D-nanomaterials printing for enhanced uniformity, quality, and dimensional precision using physics-guided artificial neural network by Anita Ghandehari, Jorge A. Tavares-Negrete, Jerome Rajendran, Qian Yi, Rahim Esfandyarpour

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A Data-Driven Intelligent Methodology for Developing Explainable Diagnostic Model for Febrile Diseases by Constance Amannah, Kingsley Friday Attai, Faith-Michael Uzoka

“…A dataset of 3914 patient records from secondary and tertiary healthcare facilities was used to train and validate predictive models, employing Random Forest, Extreme Gradient Boost, and Multi-Layer Perceptron with optimized hyperparameters. …”
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Data augmentation for numerical data from manufacturing processes: an overview of techniques and assessment of when which techniques work by Henry Ekwaro-Osire, Sai Lalitha Ponugupati, Abdullah Al Noman, Dennis Bode, Klaus-Dieter Thoben

“…Abstract Over the past two decades, machine learning (ML) has transformed manufacturing, particularly in optimizing production and quality control. …”
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Adaptive crayfish optimization algorithm for multi-objective scheduling optimization in distributed production workshops by Xin Yang, Xiaoying Yang, Jinhao Du

“…The model aims to maximize customer satisfaction, minimize total setup time, and reduce deviations in workshop machine loads. …”
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Enhanced framework for credit card fraud detection using robust feature selection and a stacking ensemble model approach by Rahul Kumar Gupta, Asmaul Hassan, Samir Kumar Majhi, Nikhat Parveen, Abu Taha Zamani, Raju Anitha, Binayak Ojha, Abhinav Kumar Singh, Debendra Muduli

“…The particle swarm optimization (PSO) algorithm is employed to optimize ELM parameters, enhancing generalization and model convergence. …”
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Comparative Model Efficiency Analysis Based on Dissimilar Algorithms for Image Learning and Correction as a Means of Fault-Finding by Joe Benganga, Tshepo Kukuni, Ben Kotze, Lepekola Lenkoe

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