Motion Gait Recognition of Lower Limb Exoskeleton Based on Particle Swarm Optimization-Based Extreme Learning Machine Algorithm by Ting Liu, Kai Liu, Wuyi Luo, Jiange Kou, Haoran Zhan, Guangkai Yu, Qing Guo, Yan Shi

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Enhancing Manufacturing Precision: Leveraging Motor Currents Data of Computer Numerical Control Machines for Geometrical Accuracy Prediction Through Machine Learning by Lucijano Berus, Jernej Hernavs, David Potocnik, Kristijan Sket, Mirko Ficko

“…In this study, we propose a novel indirect measurement method that utilizes motor current data from the controller of a Computer Numerical Control (CNC) machine in combination with machine learning algorithms to predict the geometric accuracy of machined parts in real-time. …”
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The LETBP feature descriptor based fish species classification using Kepler optimization with Extreme Learning Machine by Annalakshmi GANESAN, Sakthivel Murugan SANTHANAM

“…The extracted unique feature values are given to the Extreme Learning Machine (ELM) for the final classification. The ELM network randomly selects the bias and weights and in order to overcome this issue an optimization technique called Kepler Optimization Algorithm (KOA) is adopted. …”
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Fetal health classification with predictive algorithm by using Ensemble Model by Devi V. Sowmya, Kancharakuntla Manoj Reddy, Paleti Goutam Nayudu, Madhunala Akash

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Battery Current Estimation and Prediction During Charging with Ant Colony Optimization Algorithm by Selamat Muslimin, Ekawati Prihatini, Nyayu Latifah Husni, Tresna Dewi, Mukhidin Wartam Bin Umar, Auvi Crisanta Ana Bela, Sri Utami Handayani, Wahyu Caesarendra

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Robust Classification of UWB NLOS/LOS Using Combined FCE and XGBoost Algorithms by Shoude Wang, Nur Syazreen Ahmad

“…Preliminary NLOS identification and classification are performed using Fuzzy Comprehensive Evaluation (FCE), with subsequent optimization of FCE weights via the Pattern Search algorithm (PSa). Final classification and recognition are then achieved through XGBoost. …”
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T‐SNERF: A novel high accuracy machine learning approach for Intrusion Detection Systems by Mohamed Hammad, Nabil Hewahi, Wael Elmedany

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Machine Learning-Based Classification of Programming Logic Understanding Levels by Mouse-Tracking Heatmaps by Attaporn Khaesawad, Yosuke Fukuchi, Vibol Yem, Nobuyuki Nishiuchi

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Study on the Influence Mechanism of Machine-Learning-Based Built Environment on Urban Vitality in Macau Peninsula by Chen Pan, Jiaming Guo, Haibo Li, Jiawei Wu, Nengjie Qiu, Shengzhen Wu

“…A machine learning technique combining a real-encoded Accelerated Genetic Algorithm-Projective Pathfinding Model (RAGA-PPM) and Shapley Additive Projection for Interpretability (SHAP) for Interpretability Analysis (IPA) was used to investigate the nonlinear mechanisms of 17 factors affecting urban vitality in Macau Peninsula, China. …”
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Muses or Stereotypes? Identifying Historical Patterns of Sexism in a Corpus of Brazilian Lyrics by Janaina Nogueira de Souza Lopes, Vitória Pereira Firmino, Valéria Quadros dos Reis

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Comparative Analysis of Linear Regression and Neural Network Algorithms for Stock Price Prediction by Eldrianto Christian Wibowo, Ariya Dwika Cahyono

“…This study compares the performance of Linear Regression and Neural Network algorithms in predicting stock prices using historical data from PT Bank Central Asia Tbk (BBCA) for the period from January 1, 2019, to February 17, 2025. …”
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Non‐Autoregressive Translation Algorithm Based on LLM Knowledge Distillation in English Corpus by Fang Ju, Weihui Wang

“…So this research introduces an English corpus‐based machine translation algorithm that leverages knowledge distillation from large language model, with the goal of enhancing translation quality and reducing the computational demands of the model. …”
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Integrative analysis of signaling and metabolic pathways, immune infiltration patterns, and machine learning-based diagnostic model construction in major depressive disorder by Lei Tang, Liling Wu, Mengqin Dai, Nian Liu, Lu liu

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Leveraging multiple cell-death patterns based on machine learning to decipher the prognosis, immune, and immune therapeutic response of soft tissue sarcoma by Binfeng Liu, Shasha He, Chenbei Li, Zijian Xiong, Zhaoqi Li, Chengyao Feng, Hua Wang, Chao Tu, Zhihong Li

“…Nonetheless, the precise role of multiple cell death patterns in STS is yet to be clarified. We employed 96 machine-learning algorithm combination frameworks to identify novel cell death-related signatures (CDSigs) with the highest mean c-index, indicating their excellence. …”
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Explainable and Interpretable Model for the Early Detection of Brain Stroke Using Optimized Boosting Algorithms by Yogita Dubey, Yashraj Tarte, Nikhil Talatule, Khushal Damahe, Prachi Palsodkar, Punit Fulzele

“…The stroke pre-diction using optimized boosting machine learning algorithms is supported with explainable AI using LIME and SHAP. …”
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Machine learning classifiers to detect data pattern change of continuous emission monitoring system: A typical chemical industrial park as an example by Zhefeng Xu, Xiahong Shi, Wei Shu, Yilu Xin, Xuan Zan, Zhaonian Si, Jinping Cheng

“…By categorizing outlets into 12 datasets based on monitoring parameters, 17 machine learning models were evaluated to identify emission patterns and detect potential data anomalies. …”
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Prediction of Treatment Recommendations Via Ensemble Machine Learning Algorithms for Non-Small Cell Lung Cancer Patients in Personalized Medicine by Hojin Moon, Lauren Tran, Andrew Lee, Taeksoo Kwon, Minho Lee

“…Objectives: The primary goal of this research is to develop treatment-related genomic predictive markers for non-small cell lung cancer by integrating various machine learning algorithms that recommends near-optimal individualized patient treatment for chemotherapy in an effort to maximize efficacy or minimize treatment-related toxicity. …”
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Identifying patterns of high intraoperative blood pressure variability in noncardiac surgery using explainable machine learning: a retrospective cohort study by Zheng Zhang, Jian Wu, Yi Duan, Linwei Liu, Yaru Liu, Jinghan Wang, Li Xiao, Zhifeng Gao

“…We applied four ML algorithms—Extreme Gradient Boosting (XGBoost), Random Forest (RF), Light Gradient Boosting Machine (LightGBM), and Logistic Regression (LR)—to classify patients with or without HIBPV. …”
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Identification of novel metabolism-related biomarkers of Kawasaki disease by integrating single-cell RNA sequencing analysis and machine learning algorithms by Chenhui Feng, Zhimiao Wei, Xiaohui Li, Xiaohui Li

“…Through differential expressed genes (DEG) analysis, high-dimensional Weighted Correlation Network Analysis (hdWGCNA) and machine learning algorithms, we identified signature genes associated with both BAM and FAM. …”
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Development and Internal Validation of Machine Learning Algorithms for Predicting Subsequent Contralateral Slipped Capital Femoral Epiphysis in Patients With Unilateral Slips by David P. VanEenenaam, Jr., BS, Carter Hall, BS, Daniel A. Maranho, MD, PhD, Christopher J. DeFrancesco, MD, Eduardo N. Novais, MD, Wudbhav N. Sankar, MD

“…Background: Controversy remains about whether to pin the contralateral side in cases of unilateral slipped capital femoral epiphysis (SCFE). Machine learning (ML) algorithms can be leveraged to identify complex, nonlinear patterns in data and allow for more accurate predictions on which patients may need a prophylactic pin. …”
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