Decoding survival in MASLD: the dominant role of metabolic factors by Zhiqiang Jin, Cheng Zeng, Yang Yang, Shan Zhong, Zhi Zhou

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An Integrated Algorithm with Feature Selection, Data Augmentation, and XGBoost for Ovarian Cancer by Jingxun Cai, Zne-Jung Lee, Zhihxian Lin, Chih-Hung Hsu, Yun Lin

“…First, we can simplify the original genetic dataset through feature selection methods, removing irrelevant variables and noise, thereby improving the model’s predictive accuracy. Following dimensionality reduction, AC-GAN enriches the data, producing more realistic genetic samples to enhance the model’s generalization capacity. …”
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A Novel Method for Noise Reduction and Jump Correction of Maglev Gyroscope Rotor Signals Under Instantaneous Perturbations by Di Liu, Zhen Shi, Chenxi Zou, Ziyi Yang, Jifan Li

“…To solve this problem, we propose a novel noise reduction algorithm that integrates Moving Average Filtering with Autoregressive Integrated Moving Average (MAF-ARIMA), based on the noise characteristics of the rotor jump signal. …”
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The impact of quantitative platform on candidacy for bronchoscopic lung volume reduction: a multi-center retrospective cohort study by Max Wayne, Suchitra Pilli, Hee Jae Choi, Nathaniel Moulton, Praveen Chenna, Allen Cole Burks, Alexander Chen

“…Background: Bronchoscopic lung volume reduction (BLVR) can be an effective treatment for highly selected patients with severe emphysema but only half of carefully selected patients derive clinical benefit. …”
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Robust Design Optimization of Viscoelastic Damped Composite Structures Integrating Model Order Reduction and Generalized Stochastic Collocation by Tianyu Wang, Chao Xu, Teng Li

“…Pareto optimal solutions are determined by combining the proposed MOR and gSC approaches with a well-established Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm, which accounts for robustness in handling design variables, objectives, and constraints. …”
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An Online Tool for Correcting Performance Measures of Electronic Phenotyping Algorithms for Verification Bias by Ajay Bhasin, Sue Bielinski, Abel N. Kho, Nicholas Larson, Laura J. Rasmussen-Torvik

“… Objectives Computable or electronic phenotypes of patient conditions are becoming more commonplace in quality improvement and clinical research. During phenotyping algorithm validation, standard classification performance measures (i.e., sensitivity, specificity, positive predictive value, negative predictive value, and accuracy) are often employed. …”
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Performance comparison of machine learning algorithms for condition monitoring of tapered roller bearings by Harshal Aher, Nilesh Ghuge

“…This paper investigated the implementation of machine learning algorithms for health monitoring and fault detection of tapered roller bearings (TRBs) (30205 J2/Q, 30206 J2/Q and 30207 J2/Q). …”
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MODELLING FLUCTUATIONS OF GROUNDWATER LEVEL USING MACHINE LEARNING ALGORITHMS IN THE SOKOTO BASIN by Samson Alfa, Haruna Garba, Augustine Odeh

“…Among the models, the XGBoost algorithm demonstrated the highest performance, providing precise predictions that closely aligned with the actual groundwater levels. …”
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Mahalanobis distance–based kernel supervised machine learning in spectral dimensionality reduction for hyperspectral imaging remote sensing by Jing Liu, Yulong Qiao

“…Spectral dimensionality reduction is a crucial step for hyperspectral image classification in practical applications. …”
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An Approach to Data Reduction for Learning from Big Datasets: Integrating Stacking, Rotation, and Agent Population Learning Techniques by Ireneusz Czarnowski, Piotr Jędrzejowicz

“…We propose to use an agent-based population learning algorithm for data reduction in the feature and instance dimensions. …”
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Freedom under algorithms: how unpredictable and asocial management erodes free choice by Robert Donoghue

“…This issue is further complicated by the fact that as algorithms become more resilient and useful, their outputs grow increasingly opaque and unpredictable—what some refer to as the resilience-predictability paradox. …”
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Inverse Design of Broadband Artificial Magnetic Conductor Metasurface for Radar Cross Section Reduction Using Simulated Annealing by Haoda Xia, Xiaoyu Liang, Bowen Jia, Pei Shi, Zhihong Chen, Shi Pu, Ning Xu

“…The experimental results show a significant RCS reduction of 10 dB within the 7.6–15.5 GHz range, with the peak reduction reaching-28 dB at normal incidence. …”
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Estimating latent heat flux of subtropical forests using machine learning algorithms by Harekrushna Sahu, Pramit Kumar Deb Burman, Palingamoorthy Gnanamoorthy, Qinghai Song, Yiping Zhang, Huimin Wang, Yaoliang Chen, Shusen Wang

“…By harnessing diverse datasets, we employ various machine learning regression algorithms. We find the support vector regression superior to linear, lasso, random forest, adaptive boosting and gradient boosting algorithms. …”
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Fast optimization of the emission reduction pathways of major air pollutants in China: From the perspective of different decision preferences by Yihao Wang, Xuying Wang, Yixuan Zheng, Zeyuan Liu, Yu Zhang, Jiani Kang, Wenbo Xue, Jing Zhang, Yu Lei

“…Six emission reduction scenarios with varying decision preferences were analyzed. …”
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Dimensionality cutback and deep learning algorithms efficacy as to the breast cancer diagnostic dataset by Gennady Chuiko, Denys Honcharov

“…The results indicate that the dimensionality of the Wisconsin Breast Cancer dataset, which is increasingly becoming the "gold standard" for diagnosing Malignant-Benign tumors, can be significantly reduced without losing predictive power. The Deep Learning algorithms in WEKA deliver excellent performance for both supervised and unsupervised learning, regardless of whether dealing with full or reduced datasets.…”
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Peak Arm Current Reduction of Modular Multilevel Converter Based on Particle Swarm Optimizer for Circulating Current Injections by Riyadh Toman Thahab, Tahani Hamodi Al-Mhana

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Research on Vibration Reduction Method of Nonpneumatic Tire Spoke Based on the Mechanical Properties of Domestic cat’s Paw Pads by Haichao Zhou, Huiyun Li, Ye Mei, Guolin Wang, Congzhen Liu, Lingxin Zhang

“…The three parameters, the asymmetric arc, the thickness, and the curvature of spokes, were used as design variables to maximize the vibration reduction. The orthogonal experimental, the Kriging approximate model, and the genetic algorithm were carefully selected for optimal solutions. …”
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Security situational awareness of power information networks based on machine learning algorithms by Chao Wang, Jia-han Dong, Guang-xin Guo, Tian-yu Ren, Xiao-hu Wang, Ming-yu Pan

“…To properly predict the security posture of these networks, we provide a method based on machine learning algorithms to detect the security condition of power information networks. …”
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Performance of machine learning algorithms to evaluate the physico-mechanical properties of nanoparticle panels by Derrick Mirindi, James Hunter, David Sinkhonde, Tajebe Bezabih, Frederic Mirindi

“…This review analyzes secondary data on nanoparticle integration in board production, aiming to evaluate the relationships among physical (water absorption (WA) and thickness swelling (TS)) and mechanical (modulus of rupture (MOR), modulus of elasticity (MOE); and internal bond (IB) strength) properties and to predict performance using machine learning (ML) algorithms. …”
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Exploring the limits of scan time reduction for ferumoxytol-enhanced whole-heart angiography in congenital heart disease patients by Ludovica Romanin, Milan Prsa, Christopher W. Roy, Xavier Sieber, Jérôme Yerly, Bastien Milani, Tobias Rutz, Salim Si-mohamed, Estelle Tenisch, Davide Piccini, Matthias Stuber

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