Network intrusion detection model using wrapper based feature selection and multi head attention transformers by Muhammad Umer, Muhammad Tahir, Muhammad Sardaraz, Muhammad Sharif, Hela Elmannai, Abeer D. Algarni

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Graph feature selection for enhancing radiomic stability and reproducibility across multiple institutions in head and neck cancer by Hajar Moradmand, Jason Molitoris, Xiao Ling, Lisa Schumaker, Erin Allor, Hannah Thomas, Danielle Arons, Matthew Ferris, Rebecca Krc, William Silva Mendes, Phuoc Tran, Amit Sawant, Ranee Mehra, Daria A. Gaykalova, Lei Ren

“…We investigate a Graph-Based Feature Selection (Graph-FS) approach that models feature interdependencies to identify stable radiomic signatures for head and neck squamous cell carcinoma (HNSCC) across institutions. …”
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Exploring Feature Selection with Deep Learning for Kidney Tissue Microarray Classification Using Infrared Spectral Imaging by Zachary Caterer, Jordan Langlois, Connor McKeown, Mikayla Hady, Samuel Stumo, Suman Setty, Michael Walsh, Rahul Gomes

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Optimization of EEG-based wheelchair control: machine learning, feature selection, outlier management, and explainable AI by Amr M. Hamed, Abdel-Fattah Attia, Heba El-Behery

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Kidney Ensemble-Net: Enhancing Renal Carcinoma Detection Through Probabilistic Feature Selection and Ensemble Learning by Zaib Akram, Kashif Munir, Muhammad Usama Tanveer, Atiq Ur Rehman, Amine Bermak

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Model Input-Output Configuration Search With Embedded Feature Selection for Sensor Time-Series and Image Classification by Anh Tuan Hoang, Zsolt Janos Viharos

Subjects: “…Feature selection…”
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MEF-AlloSite: an accurate and robust Multimodel Ensemble Feature selection for the Allosteric Site identification model by Sadettin Y. Ugurlu, David McDonald, Shan He

Subjects: “…Multimodel Ensemble Feature selection…”
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Topological search and gradient descent boosted Runge–Kutta optimiser with application to engineering design and feature selection by Jinge Shi, Yi Chen, Ali Asghar Heidari, Zhennao Cai, Huiling Chen, Guoxi Liang

“…Additionally, the evaluation includes real‐world engineering design and feature selection problems serving as an additional test for assessing the optimisation capabilities of the algorithm. …”
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Defining a radiomics feature selection method for predicting response to transarterial chemoembolization in hepatocellular carcinoma patients by Helen Zhang, Li Yang, Amanda Laguna, Jing Wu, Beiji Zou, Alireza Mohseni, Rajat S. Chandra, Tej I. Mehta, Hossam A. Zaki, Paul Zhang, Zhicheng Jiao, Ihab R. Kamel, Harrison X. Bai

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Robust multi-task feature selection with counterfactual explanation for schizophrenia identification using functional brain networks by Xinyan Yuan, Shaolong Wei, Ying Sun, Lingling Gu, Yanyan He, Tiantian Chen, Hongcheng Yao, Haonan Rao

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A precise machine learning model: Detecting cervical cancer using feature selection and explainable AI by Rashiduzzaman Shakil, Sadia Islam, Bonna Akter

“…The decision tree outperformed in Chi-square feature selection with outstanding accuracy with 97.60%, 98.73% sensitivity, 80% specificity, and 98.73% precision, respectively. …”
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A Novel Ensemble Feature Selection Technique for Cancer Classification Using Logarithmic Rank Aggregation Method by Hüseyin Öztoprak, Hüseyin Güney

“…Recent studies have shown that ensemble feature selection (EFS) has achieved outstanding performance in microarray data classification. …”
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Fine Resolution Mapping of Forest Soil Organic Carbon Based on Feature Selection and Machine Learning Algorithm by Yanan Li, Jing Li, Jun Tan, Tianyue Ma, Xingguang Yan, Zongyang Chen, Kunheng Li

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An ensemble deep learning framework for energy demand forecasting using genetic algorithm-based feature selection. by Mohd Sakib, Tamanna Siddiqui, Suhel Mustajab, Reemiah Muneer Alotaibi, Nouf Mohammad Alshareef, Mohammad Zunnun Khan

“…This study proposes an ensemble approach that integrates a genetic algorithm with multiple forecasting models to optimize feature selection. The genetic algorithm identifies the optimal subset of features from a dataset that includes historical energy consumption, weather variables, and temporal characteristics. …”
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Enhancing Hybrid Classification for Plant Diseases With Deep Feature Selection Based on Analytical Entropy and Statistical Method by Phanthawat Phiphatkamtorn, Sutasinee Jitanan

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Enhanced framework embedded with data transformation and multi-objective feature selection algorithm for forecasting wind power by Yahya Z. Alharthi, Haruna Chiroma, Lubna A. Gabralla

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A Classification Method for E-mail Spam Using a Hybrid Approach for Feature Selection Optimization by Zeinab Hassani, vahid Hajihashemi, Keivan Borna, Iman Sahraei Dehmajnoonie

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Optimizing radiomics for prostate cancer diagnosis: feature selection strategies, machine learning classifiers, and MRI sequences by Eugenia Mylona, Dimitrios I. Zaridis, Charalampos Ν. Kalantzopoulos, Nikolaos S. Tachos, Daniele Regge, Nikolaos Papanikolaou, Manolis Tsiknakis, Kostas Marias, ProCAncer-I Consortium, Dimitrios I. Fotiadis

“…Best feature selection methods: RFE, LASSO, RF, and Boruta. …”
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Performance Analysis and Improvement of Machine Learning with Various Feature Selection Methods for EEG-Based Emotion Classification by Sherzod Abdumalikov, Jingeun Kim, Yourim Yoon

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Dynamic Multi-Level Competition Learning-Based Dual-Task Optimization for High-Dimensional Feature Selection by Weiwei Zhang, Yiwei Zhao, Chunbo Yuan, Xiaolong Chen, Wenzhao Liu, Yingjie Feng, Yongxin Feng, Jinchu Yang, Meng Li

Subjects: “…Feature selection (FS)…”
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