A Seasonal Fresh Tea Yield Estimation Method with Machine Learning Algorithms at Field Scale Integrating UAV RGB and Sentinel-2 Imagery by Huimei Liu, Yun Liu, Weiheng Xu, Mei Wu, Leiguang Wang, Ning Lu, Guanglong Ou

“…Subsequently, these 26 features were screened using the random forest algorithm and Pearson correlation analysis. …”
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Inferring regulatory networks by combining perturbation screens and steady state gene expression profiles. by Ali Shojaie, Alexandra Jauhiainen, Michael Kallitsis, George Michailidis

“…The proposed approach is based on a three-step algorithm to estimate the underlying directed but cyclic network, that uses as input both perturbation screens and steady state gene expression data. …”
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Design and evaluation of screening and self-care (mobile) application for oral and dental problems and emergencies by Sedighe Sadat Hashemikamangar, Aidin Sooratgar, Mina Khayamzadeh, Shayan Momeni, Ali Asghar Safaei, Behnaz Behniafar

“…Materials and method: A system made up of web and mobile apps is proposed and evaluated for screening and self-care of oral and dental problems and for providing advice on dental emergencies and therapeutic measures. …”
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Screening of serum biomarkers in patients with PCOS through lipid omics and ensemble machine learning. by Ji-Ying Chen, Wu-Jie Chen, Zhi-Ying Zhu, Shi Xu, Li-Lan Huang, Wen-Qing Tan, Yong-Gang Zhang, Yan-Li Zhao

“…Three machine learning models, logistic regression, random forest, and support vector machine, showed that screened biomarkers had better classification ability and effect. …”
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Improvement of the Diagnostics of the Fetus Heart Anomalies During a Routine Screening Ultrasound Examination by Markin L., Medvjedjeva O.

“…In our opinion, the prenatal detection of congenital heart defects strongly depends on the algorithm of conducting a fetal heart study in the screening regimen. …”
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Development of Electronic Nose as a Complementary Screening Tool for Breath Testing in Colorectal Cancer by Chih-Dao Chen, Yong-Xiang Zheng, Heng-Fu Lin, Hsiao-Yu Yang

“…We then used machine learning algorithms to develop predictive models and provided the estimated accuracy and reliability of the breath testing. (3) Results: We enrolled 77 patients, with 40 cases and 37 controls. …”
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Targeted Detection of 76 Carnitine Indicators Combined with a Machine Learning Algorithm Based on HPLC-MS/MS in the Diagnosis of Rheumatoid Arthritis by Rui Zhang, Juan Wang, Xiaonan Zhai, Yuanbing Guo, Lei Zhou, Xiaoyan Hao, Liu Yang, Ruiqing Xing, Juanjuan Hu, Jiawei Gao, Fengjuan Wang, Jun Yang, Jiayun Liu

“…The diagnostic model derived from the screened markers was validated using three machine learning algorithms. …”
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Short-Term Photovoltaic Power Combined Prediction Based on Feature Screening and Weight Optimization by Liqing Geng, Yadong Yang, Genghuang Yang, Yongfeng Zheng, Xiaocong Liu

“…Aiming at the problem of low prediction accuracy caused by the intermittent and fluctuating characteristics of photovoltaic power, a short-term photovoltaic power combined prediction method based on feature screening and weight optimization is proposed. Firstly, K-means is used to cluster the photovoltaic power; Secondly, CEEMDAN is used to decompose photovoltaic power and wavelet decomposition is used to decompose irradiance, and sample entropy and K-means are used to reconstruct each component of photovoltaic power into high, intermediate, and low frequency terms; Then, Spearman’s correlation coefficient is used to calculate the correlation between each meteorological factor and the decomposed irradiance component and the high, intermediate, and low frequency terms of photovoltaic power, and the feature selection is carried out; Then, CNN-BiLSTM-Attention is used to predict the high frequency term, LSTM is used to predict the intermediate frequency and low frequency terms, and the results are superimposed to obtain the preliminary prediction value; Finally, the dung beetle algorithm is used to optimize the weights of the initial prediction values of the training set of high, intermediate, and low frequency terms, and the optimal weight is substituted into the test set to obtain the final prediction result. …”
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Reflective Distributed Denial of Service Detection: A Novel Model Utilizing Binary Particle Swarm Optimization—Simulated Annealing for Feature Selection and Gray Wolf Optimization-... by Daoqi Han, Honghui Li, Xueliang Fu

“…The BPSO-SA algorithm enhances the global search capability of Particle Swarm Optimization (PSO) using the SA mechanism and effectively screens out the optimal feature subset; the GWO algorithm optimizes the hyperparameters of LightGBM by simulating the group hunting behavior of gray wolves to enhance the detection performance of the model. …”
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Round reduction-based fault attack on SM4 algorithm by Min WANG, Zhen WU, Jin-tao RAO, Hang LING

“…A novel method of fault attack based on round reduction against SM4 algorithm was proposed.Faults were in-jected into the last four rounds of the SM4 encryption algorithm,so that the number of the algorithm's rounds can be re-duced.In known-ciphertext scenario,four traces are enough to recover the total 128 bit master key by screening these faults easily.The proposed attack is made to an unprotected SM4 smart card.Experiment shows that this attack method is efficient,and which not only simplifies the existing differential fault attack,but also improves the feasibility of the attack.…”
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Lightweight Detection Algorithm for Breast-Mass Features in Ultrasound Images by Taojuan Li, Wen Liu, Mingxian Song, Zheng Gu, Ling Hai

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Domain name generation algorithm based on improved Markov chain by QIAN Zhiye, LI Xue, LI Suogang

“…Then, the improved Markov model algorithm was used to analyze the filtered data, and new subdomain names were generated and added to the result set. …”
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Application of Artificial Intelligence Algorithms in the Field of Antimicrobial Peptide Prediction by QIAN Yuchen, NIE Ting, HUA Yanming, XU Shiying, GUO Sheng, ZHANG Xin, LUO Xiaohu, LIU Yanan

“…Currently, several specialized databases have been established, providing rich resources for algorithmic model training. Furthermore, multi-source bioinformatics data such as genomics, transcriptomics and proteomics are also widely used to predict antimicrobial peptides, with a view to identifying peptides with potential antimicrobial activity more accurately. …”
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Laryngeal cancer diagnosis based on improved YOLOv8 algorithm by Xin Nie, Xueyan Zhang, Di Wang, Yuankun Liu, Lumin Xing, Wenjian Liu

“…A novel multiscale enhanced convolution module has been introduced to improve the model’s feature extraction capabilities for small-sized targets. …”
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Analysis of E-Commerce Marketing Strategy Based on Xgboost Algorithm by Hong Chen, Wei Wan

“…This paper reviews the current literature on e-commerce marketing and then analyzes the feasibility of precision marketing in e-commerce market in the new media era. In order to screen potential consumers and improve the success rate of precision marketing, this paper establishes a prediction model for precision marketing of bank credit cards. …”
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Electricity Load Forecasting Method Based on the GRA-FEDformer Algorithm by Xin Jin, Tingzhe Pan, Heyang Yu, Zongyi Wang, Wangzhang Cao

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Blinded Validation of Breath Biomarkers of Lung Cancer, a Potential Ancillary to Chest CT Screening. by Michael Phillips, Thomas L Bauer, Renee N Cataneo, Cassie Lebauer, Mayur Mundada, Harvey I Pass, Naren Ramakrishna, William N Rom, Eric Vallières

“…Outcome modeling: We modeled the expected effects of combining breath biomarkers with chest CT on the sensitivity and specificity of lung cancer screening.…”
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The urgency of the androgenic screening for men who underwent preventive medical examination for prostate diseases detection by A. A. Kamalov, M. Ye. Chaly, R. P. Vasilevsky

“…The bad influence of the androgenic insufficiency for men defines the need for obligatory androgenic screening of more than 50 years old patients. Testosterone level was examined. …”
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Artificial intelligence for screening and early diagnosis of pancreatic neoplasms in the context of centralization of the laboratory service in the region by S. I. Panin, V. A. Suvorov, A. V. Zubkov, S. A. Bezborodov, A. A. Panina, N. V. Kovalenko, A. R. Donsckaia, I. G. Shushkova, A. V. Bykov, Ya. A. Marenkov

“…Determination of the optimal machine learning model for the creation of software for screening and early diagnosis of pancreatic neoplasms in the context of centralization of the laboratory service in the region. …”
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A Novel Method for Screening the PMU Phase Angle Difference Data Based on Hyperplane Clustering by Ancheng Xue, Shuang Leng, Yecheng Li, Feiyang Xu, Kenneth E. Martin, Jingsong Xu

“…First, we develop the hyperplane cluster method to cluster the phase angle difference data. Second, in order to screen out the right data type, this paper compares the virtual reactance parameters of each data type obtained by voltage mean to the line reactance parameter given by the system model. …”
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