基于脑影像及临床特征的机器学习模型预测缺血性卒中后心房颤动 A Machine Learning Model Based on Brain Imaging and Clinical Features for Predicting Atrial Fibrillation Detected after Stroke... by 张栗源1，刘涛2，姜勇1，李子孝1，3，王拥军1，3，杨晓萌1，3(ZHANG Liyuan1, LIU Tao2, JIANG Yong1, LI Zixiao1,3, WANG Yongjun1,3, YANG Xiaomeng1,3 )

“…Using the LASSO algorithm for feature selection, 31 multimodal features (including 25 imaging and 6 clinical features) were obtained after screening, with an average AUC of 0.73 (95%CI 0.70-0.77). …”
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Analysis and Prediction of CET4 Scores Based on Data Mining Algorithm by Hongyan Wang

“…The weight K of the input feature and the adjacent feature are weighted, although the allocation algorithm of the adjacent classification effect has not been significantly improved, but the stability classification is better than K-nearest neighbor algorithm, its classification efficiency is greatly improved, classification time is greatly reduced, and classification efficiency is increased by 119%. …”
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Dynamic analysis of malicious behavior propagation based on feature selection in software network by Huajian Xue, Huajian Xue, Yali Wang, Qiguang Tang

“…This paper introduces a dynamic analysis detection method for malicious behavior based on feature extraction (MBDFE), designed to effectively identify and thwart the spread of malicious software. …”
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Parkinson’s Disease Detection Based on Transfer Learning by Mohammad Talal Ghazal

“…In this research, a method was developed to detect Parkinson's disease using machine learning,  learning transfer techniques were relied upon to extract features from handwriting images that we obtained from the NewHandPD database, and then these images were classified into two categories (Parkinson's disease and non-Parkinson's disease) by KNN classification algorithm, for being accurate and fast in calculations, the results  of the  training of the INCEPTION-V4 model showed  a detection accuracy of up to 93%, as well as an area under the curve of 0.89 with a loss of only 0.2 , where this model can be relied on to diagnose and detect Parkinson's disease with high accuracy. …”
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Design and implementation algorithm of safe driver assistant system based on EOG by Zhao LYU, Xiao-pei WU, Chao ZHANG, Bing WEI

“…Furthermore, independent component analysis (ICA) algorithm was used to extract spatial feature parameters of activity-detected EOG signals, and combined with support vector machine (SVM) method to recognize the type of saccade signals, such as up-rolling, left-rolling and right-rolling. …”
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Adaptive GDDA-BLAST: fast and efficient algorithm for protein sequence embedding. by Yoojin Hong, Jaewoo Kang, Dongwon Lee, Damian B van Rossum

“…Herein, we describe the logic and algorithmic process for a heuristic embedding strategy named "Adaptive GDDA-BLAST." …”
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Machine learning–based feature prediction of convergence zones in ocean front environments by Weishuai Xu, Lei Zhang, Hua Wang

“…Furthermore, among the input features, the turning depth emerged as a crucial determinant, contributing more than 25% to the model’s effectiveness in predicting the convergence zone’s distance. …”
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Dynamic primary user spectrum sensing algorithm based on deep learning by Li Xinyu, Zhao Zhijin

“…The proposed algorithm can maintain a high detection probability for the primary users who randomly arrive or leave following different distributions.…”
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Research on lightweight weed recognition algorithm based on improved YOLOv8 by Zhang Chao, Liu Bin, Li Kun

“…Then, Effcient-RepGFPN is introduced as the neck network, and RFAConv is used to replace the two CSPStage modules before up-sampling. Different scale features are used to improve the performance of target detection. …”
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Research on Semantic Segmentation Algorithm for Infrared Moving Targets in Complex Backgrounds by Ji Haoyu, Meng Weihua, Zhang Xinchao, Duan Jingfei, Zhang Meng

“…Based on the publicly available target detection and tracking dataset, an infrared image semantic segmentation dataset is annotated and constructed. …”
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ALGORITHM OF PREPARATION OF THE TRAINING SAMPLE USING 3D-FACE MODELING by D. I. Samal, I. I. Frolov

“…The preparation and preliminary processing of images contains the following constituents like detection and localization of area of the person on the image, assessment of an angle of rotation and an inclination, extension of the range of brightness of pixels and an equalization of the histogram to smooth the brightness and contrast characteristics of the processed images, scaling of the localized and processed area of the person, creation of a vector of features of the scaled and processed image of the person by a Principal component analysis (algorithm NIPALS), training of the multiclass SVM-classifier.The provided algorithm of expansion of the training selection is oriented to be used in practice and allows to expand using 3D-models the processed range of 2D – photographs of persons that positively affects results of identification in system of face recognition. …”
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Honeyword Generation Using a Proposed Discrete Salp Swarm Algorithm by Yasser A. Yasser, Ahmed T. Sadiq, Wasim AlHamdani

“…The honeyword system is an effective password cracking detection system designed to easily detect password cracking in order to improve the security of hashed passwords. …”
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Development and Validation of an Ultrasound Imaging Algorithm for Structured Reporting in Testicular Pathology by Roxana Pintican, Alexandru Negrea, Isabell Boll, Bianca Boca, Diana Gherman, Marilena Bora, Sorin Dudea, Anca Ciurea

“…<b>Conclusions</b>: This study shows that the proposed diagnostic algorithm is an effective tool for testicular US, facilitating accurate and reproducible assessments, which are crucial for early detection and optimal management of testicular pathologies.…”
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Thermal Runaway Warning of Lithium Battery Based on Electronic Nose and Machine Learning Algorithms by Zilong Pu, Miaomiao Yang, Mingzhi Jiao, Duan Zhao, Yu Huo, Zhi Wang

“…Characteristic gas detection can be an efficient way to predict the degree of thermal runaway of a lithium battery. …”
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Multimodal Data Fusion for Precise Lettuce Phenotype Estimation Using Deep Learning Algorithms by Lixin Hou, Yuxia Zhu, Mengke Wang, Ning Wei, Jiachi Dong, Yaodong Tao, Jing Zhou, Jian Zhang

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Integrating Explanations into CNNs by Adopting Spiking Attention Block for Skin Cancer Detection by Inzamam Mashood Nasir, Sara Tehsin, Robertas Damaševičius, Rytis Maskeliūnas

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Crop row centerline extraction method based on regional feature point clustering by Baofeng Ji, Hang Wang, Chunhong Dong, Song Chen, Hongtao Chen, Fazhan Tao, Ji Zhang, Huitao Fan

“…Next, Harris corner detection technology is used to extract crop feature points, and these feature points are clustered using the DBSCAN algorithm, marking each crop row with a different color. …”
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A Comparative Evaluation of Texture Features for Semantic Segmentation of Breast Histopathological Images by R. Rashmi, Keerthana Prasad, Chethana Babu K. Udupa, V. Shwetha

“…Support Vector Machine and Multi Layer Perceptron algorithms are trained to perform pixelwise classification. …”
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Extracting Optimal Number of Features for Machine Learning Models in Multilayer IoT Attacks by Badeea Al Sukhni, Soumya K. Manna, Jugal M. Dave, Leishi Zhang

“…Therefore, this research aims to develop a Semi-Automated Intrusion Detection System (SAIDS) that integrates efficient feature selection, feature weighting, normalisation, visualisation, and human–machine interaction to detect and identify multilayer attacks, enhancing mitigation strategies. …”
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Concrete Crack Skeleton Analysis: A Machine Vision Approach to Feature Extraction by Rui Wang, Xinxin Guo, Jiaxuan Liu, Yu Wan

“…The crack feature is the key to crack recognition in concrete surface crack detection systems based on machine vision. …”
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