Machine Learning-Based Ensemble Feature Selection and Nested Cross-Validation for miRNA Biomarker Discovery in Usher Syndrome by Rama Krishna Thelagathoti, Dinesh S. Chandel, Wesley A. Tom, Chao Jiang, Gary Krzyzanowski, Appolinaire Olou, M. Rohan Fernando

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A deep learning framework for gender sensitive speech emotion recognition based on MFCC feature selection and SHAP analysis by Qingqing Hu, Yiran Peng, Zhong Zheng

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A Novel Scheme for Improving Accuracy of KNN Classification Algorithm Based on the New Weighting Technique and Stepwise Feature Selection by Saeid Sheikhi, Mohammad Taghi Kheirabadi, Amin Bazzazi

“…Then a new weighting method was proposed to give authority value to each sample in train dataset based on neighbor categories and Euclidean distances. …”
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The value of radiomics features of white matter hyperintensities in diagnosing cognitive frailty: a study based on T2-FLAIR imaging by Qinmei Liao, Xihao Hu, Zhiqiong Jiang, Xiaoyun Huang, Jiacheng Guo, Yuanzhong Zhu, Wenjing He

“…Following an 8:2 ratio, the patients were randomly divided into training and testing sets. Repeated 5-fold cross-validation was adopted for model training and evaluation. …”
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Development of intelligent tools to predict neuroblastoma risk stratification and overall prognosis based on multiphase enhanced CT and clinical features by Wei Zhao, Yahui Han, Xiaokun Yu, Jianing Liu, Jiao Zhang, Juan Li

“…Four risk stratification classifiers were developed using the Swin Transformer model and evaluated in training and testing cohorts. Prognostic models were constructed using a combination of multiple machine learning algorithms in conjunction with CT image features and clinical characteristics.ResultsSwin-ART based on arterial phase images was the best risk stratification classifier with an AUC of 0.770 (95% CI: 0.613–0.909) and an accuracy of 0.780 in the testing cohort. …”
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Machine Learning Model for Predicting Pathological Invasiveness of Pulmonary Ground‐Glass Nodules Based on AI‐Extracted Radiomic Features by Guozhen Yang, Yuanheng Huang, Huiguo Chen, Weibin Wu, Yonghui Wu, Kai Zhang, Xiaojun Li, Jiannan Xu, Jian Zhang

“…This study aimed to develop a machine learning (ML)–based model using artificial intelligence (AI)‐extracted CT radiomic features to predict the invasiveness of GGNs. …”
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Integrated feature selection-based stacking ensemble model using optimized hyperparameters to predict breast cancer with smart web application by Rajib Kumar Halder, Marzana Akter Lima, Mohammed Nasir Uddin, Md.Aminul Islam, Adri Saha

“…These features are then used to train the model, ensuring that our approach focuses on the most relevant data points for breast cancer classification. …”
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An Anomaly Node Detection Method for Wireless Sensor Networks Based on Deep Metric Learning with Fusion of Spatial–Temporal Features by Ziheng Wang, Miao Ye, Jin Cheng, Cheng Zhu, Yong Wang

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Signal Distinction Electroencephalograms (EEG) Using a Back Propagation Neural Network Based On Localized Structural Features Extractions by Najlaa Safar

“…In this research, it localized structural feature selection method has been used as a base of quantifying structural changes with time for Electroencephalograms (EEG) obtained from four states two patient and two healthy with eyes open and eyes closed in both. …”
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Slim multi-scale convolutional autoencoder-based reduced-order models for interpretable features of a complex dynamical system by Philipp Teutsch, Philipp Pfeffer, Mohammad Sharifi Ghazijahani, Christian Cierpka, Jörg Schumacher, Patrick Mäder

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REMAINING USEFUL LIFE OF ROLLING BEARING BASED ON t⁃SNE by ZHONG JianHua, HUANG Cong, ZHONG ShunCong, XIAO ShunGen

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Clinical and imaging features of co-existent pulmonary tuberculosis and lung cancer: a population-based matching study in China by Fan Zhang, Fei Qi, Yi Han, Hongjie Yang, Yishuo Wang, Guirong Wang, Yujie Dong, Hongxia Li, Yuan Gao, Hongmei Zhang, Tongmei Zhang, Liang Li

“…This study aimed to investigate the clinical and radiological features of patients diagnosed with PTB-LC. Methods Patients diagnosed with active PTB-LC (APTB-LC), inactive PTB-LC (IAPTB), and LC alone without PTB between 2010 and 2022 at our institute were retrospectively collected and 1:1:1 matched based on gender, age, and time of admission. …”
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Predictive models of recurrent implantation failure in patients receiving ART treatment based on clinical features and routine laboratory data by Qunying Fang, Zonghui Qiao, Lei Luo, Shun Bai, Min Chen, Xiangjun Zhang, Lu Zong, Xian-hong Tong, Li-min Wu

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Robust UAV Target Tracking Algorithm Based on Saliency Detection by Hanqing Wu, Weihua Wang, Gao Chen, Xin Li

“…In response to this problem, this paper proposes a robust UAV target tracking algorithm based on saliency detection (SDBCF). Using saliency detection methods, the DCF tracker is optimized in three aspects to enhance the robustness of the tracker in complex scenes: feature fusion, filter-model construct, and scale-estimation methods improve. …”
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Machine learning-based voice assistant: optimizing the efficiency of speech conversion for people with speech disorders by M.H. Antor, N.V. Chudinovskikh, M.V. Bachurin, A.A. Shurpikov, N.A. Khlebnikov, B.A. Bredikhin

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Effective classification for neonatal brain injury using EEG feature selection based on elastic net regression and improved crow search algorithm by Ling Li, Tao Yue, Hui Wu, Yanping Zhao, Qinmei Liu, Hairong Zhang, Wei Xu

“…However, classification methods that utilise all features from the original EEG signals may result in lengthy training and classification times, thereby reducing the performance of the classification system. …”
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Classification Model of Clock Drawing Test Based on Contrastive Learning Using Multi-Channel Features With Channel-Spatial Attention by Changsu Kang, Bohyun Wang, J. S. Lim

“…The Clock Drawing Test (CDT) is a professional examination that can detect cognitive impairments, such as Parkinson’s and Alzheimer’s diseases, based on scoring criteria. The pooling layers of a convolutional neural network (CNN) compress features by reducing dimensionality, which tends to focus on a single dominant element. …”
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Classification and identification of pest, diseases and nutrient deficiency in paddy using layer based EMD phase features with decision tree by A. Pushpa Athisaya Sakila Rani, N. Suresh Singh

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A Deep Learning-Based Gunshot Detection IoT System with Enhanced Security Features and Testing Using Blank Guns by Tareq Khan

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Identifying optimized spectral and spatial features of UAV-based RGB and multispectral images to improve potato nitrogen content estimation by Hang Yin, Haibo Yang, Yuncai Hu, Fei Li, Kang Yu

“…Incorporating RGB-based texture features and MS-based spectral indices into the VHGPR model achieved the highest prediction accuracy (RMSE = 0.29%). …”
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