An ensemble machine learning-based performance evaluation identifies top In-Silico pathogenicity prediction methods that best classify driver mutations in cancer by Subrata Das, Vatsal Patel, Shouvik Chakravarty, Arnab Ghosh, Anirban Mukhopadhyay, Nidhan K. Biswas

“…Classifiers built using these top 11 PCSAs (DEOGEN2, Integrated_fitCons, MVP, etc.) demonstrated significantly higher performance (p-value < 2.22e-16) compared to those using the remaining 30 PCSAs across all three ML algorithms, in separating pathogenic driver from benign passenger mutations. …”
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Fractional analysis for heat consumption of CuO-based hybrid nanofluid via integral transform by Firas Ghanim, Ali Hasan Ali, Ghassan Ezzulddin Arif, Ali Raza

“…Several numerical techniques, such as Stehfest's and Tzou's algorithms, and the integral transform method, also known as Laplace transformation, are used to examine the approximate solution of the governed PDEs. …”
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Structural integrity and hybrid ANFIS-PSO modeling of the corrosion rate of ductile irons in different environments by Ukoba K., Akinribide O.J., Adeleke O.

“…The integrated hybrid ANFIS-PSO model revealed a sharp rise in localized corrosion caused by chloride-induced structural deterioration at the nanoscale for some of the grains. …”
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Unveiling PANoptosis in Acute Kidney Injury: An Integrative Multi-Dimensional Approach to Identify Key Biomarkers by Wang N, Zhang L, Xu Z, Xu Q, Lu Y, Niu P, Yan L, Wang L, Cao H, Shao F

“…ScRNA-seq revealed heterogeneity in PANoptosis activity across cell types. Integration of transcriptomic data with machine learning algorithms led to the identification of five key upregulated genes: EGR1, CEBPD, HSPA1A, HSPA1B, and RHOB. …”
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Verification of subclinical carotid atherosclerosis as part of risk stratification in overweight and obesity: the role of machine learning in the development of a diagnostic algori... by M. A. Druzhilov, T. Yu. Kuznetsova, D. V. Gavrilov, A. V. Gusev

“…A significant superiority of ML models was revealed in the study of available clinical and paraclinical parameters. Integration of ML mathematical models into a diagnostic algorithm for making a decision to refer a low-risk patient for extracranial artery ultrasound will significantly improve its accuracy and cost efficiency.…”
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Design and application research of traditional Chinese medicine teaching resource recommendation system based on multivariate data mining driven algorithm by Wei Zhang, Yaqing Liu, Qiang Zhang, Xiaomin Chen

“…The study uses a hybrid recommendation algorithm, combines collaborative filtering with content filtering, and integrates it into the knowledge graph of traditional Chinese medicine to realize in-depth data mining. …”
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Computational fluid dynamics and machine learning integration for evaluating solar thermal collector efficiency -Based parameter analysis by Xiaoyu Hu, Lanting Guo, Jiyuan Wang, Yang Liu

“…Abstract The present paper provides a novel hybrid computational framework that integrates Computational Fluid Dynamics (CFD) with advanced machine learning techniques to optimize solar thermal collectors employing micro-heat pipe arrays (MHPA) for food dehydration applications. …”
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LPBSA: Pre-clinical data analysis using advanced machine learning models for disease prediction by Dana R. Hamad, Tarik A. Rashid

“…The current study introduces an optimization algorithm, Learner Performance-Based Behavior with Simulated Annealing (LPBSA), integrated with Multilayer Perceptron (MLP) as a neural network technique to improve disease prediction accuracy. …”
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Enhancing Load frequency control in power systems using Puma Optimizer – Proportional Integral Derivative Method by Trung Kien Do, Thanh Long Duong

“…The simulation results show that the integral time absolute error (ITAE) value of the proposed PO method is smaller by 5.25%, 18.16%, 28.35%, and 59.92% compared to Particle Swarm Optimization (PSO), Crested Porcupine Optimization (CPO), Newton-Raphson-based optimization (NRBO), and Global Neighborhood Algorithm (GNA), respectively. …”
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IDEEA: information diffusion model for integrating gene expression and EEG data in identifying Alzheimer’s disease markers by Enes Ozelbas, Tuba Sevimoglu, Tamer Kahveci

“…Subsequently, we employ a genetic algorithm approach to integrate the distinct features of the preprocessed data. …”
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STOCK PRICE PREDICTION AND SIMULATION USING GEOMETRIC BROWNIAN MOTION-KALMAN FILTER: A COMPARISON BETWEEN KALMAN FILTER ALGORITHMS by Dimas Avian Maulana, A'yunin Sofro, Danang Ariyanto, Riska Wahyu Romadhonia, Affiati Oktaviarina, Mohammad Dian Purnama

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UAV Path Planning: A Dual-Population Cooperative Honey Badger Algorithm for Staged Fusion of Multiple Differential Evolutionary Strategies by Xiaojie Tang, Chengfen Jia, Zhengyang He

“…To address the challenges of low optimization efficiency and premature convergence in existing algorithms for unmanned aerial vehicle (UAV) 3D path planning under complex operational constraints, this study proposes an enhanced honey badger algorithm (LRMHBA). …”
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Ultrasound combined with serological markers for predicting neonatal necrotizing enterocolitis: a machine learning approach by Yi Yang, Shoulan Zhou, Xiaomin Liu, Yanhong Zhang, Liping Lin, Chenhan Zheng, Xiaohong Zhong

“…Explainable AI (XAI) using SHAP values was employed to identify key predictive features.ResultsXGBoost demonstrated the highest performance (AUC = 0.97, 95% CI: 0.92–0.99) during cross-validation. …”
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Genetic algorithm application in multi-objective optimization of structural parameters and PID controller parameters on bus driver seat's suspension system by Pham Ngoc Dai

“…The elastic element's stiffness kd (N/m) and the damper's damping coefficient cd (Ns/m) are optimized by the Pareto Method with the objective function J(x) designed by the Weighted Square Sum method, and the min value of J(x) is found with the genetic algorithm (GA). …”
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Intelligent algorithm-based model for predicting mass transfer performance in CO2 absorption within a rotating packed bed by Wei Zhang, Hao Chen, Ke Huang, Xing Shu, Cheng Fu, Bin Huang

“…Using dimensional analysis, key factors are transformed into dimensionless numbers, which are then input into models integrating least squares support vector machine (LSSVM) with genetic algorithm (GA), particle swarm optimization (PSO), and a hybrid GA-PSO (HGAPSO). …”
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An interval Type-2 fuzzy Fractional-Order PD-PI controller for frequency stabilization of islanded microgrids optimized with CO algorithm by Siavash Shirali, Saeed Zolfaghari Moghaddam, Mortaza Aliasghary

“…The CO algorithm also achieves an optimal ITAE objective value of 0.0001092, outperforming other optimization techniques.…”
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Matrix Modeling of the Selection of Electric Generators for Home Use Based on the Analytical Hierarchical Process (AHP) Algorithm in War Conditions in Ukraine by Barbara Dybek, Igor Ilge, Serhiy Zaporozhtsev, Adam Koniuszy, Grzegorz Wałowski

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Integrative bioinformatics analysis identifies METTL1 as a regulator of immune infiltration and prognosis in breast cancer by Xiao-bin Lin, Yu-zhi Yao, Hong-min Ma, Cai-rong Zhu, Qi-rong Wen

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Load demand forecasting in air conditioning a rotor Hopfield neural network approach optimized by a new optimization algorithm by Mingguang Liu, Weibo Zhao, Ying Zhou, Mahdiyeh Eslami

“…The current research provides load demand prediction by a new modified rotor Hopfield neural network (RHNN) integrated with a fractional order of seasons optimization algorithm (FO-SOA) to overcome the challenge of predicting load demand. …”
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Machine Learning-Enabled Prediction and Optimization of Sulfur Recovery Units: A Step towards Industry 4.0 Integration by Imran Khan, Husnain Saghir, Muhammad Ahsan

“…Sulfur recovery units are integral to the oil and gas industry, addressing the release of hazardous gases, particularly hydrogen sulfide. …”
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