The use of pretrained neural networks for solving the problem of reverse searching of X-ray images of prohibited items and substances by A. K. Volkov, L. V. Mironova, S. E. Potapova

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Using machine learning algorithms to predict colorectal cancer by Xingjian Xiao, Bo Hong, Kubra Maqsood, Xiaohan Yi, Guoqun Xie, Hailei Zhao, Bo Sun, Jianying Mao, Shiyou Liu, Xianglong Xu

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Using machine learning algorithms to predict colorectal polyps by Xingjian Xiao, Shiyou Liu, Kubra Maqsood, Xiaohan Yi, Guoqun Xie, Hailei Zhao, Bo Sun, Jianying Mao, Xianglong Xu

“…Interpretation: Using non-invasive factors and machine learning algorithms can accurately predict the occurrence of colorectal polyps in individuals with positive initial screening results. …”
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Machine learning algorithms reveal the secrets of mitochondrial dynamics by Jack J Collier, Robert W Taylor

“…In this issue of EMBO Molecular Medicine, supervised machine learning algorithms underlie a novel tool that enables automated, high throughput and unbiased screening of changes in mitochondrial morphology measured using confocal microscopy. …”
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Development and Clinical Validation of Visual Inspection With Acetic Acid Application-Artificial Intelligence Tool Using Cervical Images in Screen-and-Treat Visual Screening for Ce... by Usha Rani Poli, Anirudh G. Gudlavalleti, Jaya Bharadwaj Y, Hira B. Pant, Varun Agiwal, G.V.S. Murthy

“…The perceived challenge rate for false positives was 20%.CONCLUSIONThis novel cervical image–based VIA-AI algorithm showed promising results in real-life settings, and could help minimize overtreatment in single-visit VIA screening and treatment programs in resource-constrained situations.…”
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Algorithm for alerting the unmanned aerial vehicle operator based on the image potential obstacle borders detection on the flight trajectory using the OPEN CV library by V. Yu. Stepanov, E. A. Hvitko

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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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A monthly runoff prediction model based on ICEEMD-L-SHADE-SRU by Ziyang Kou, Yang Yang, Zhiping Li, Xiaoshuang Fu

“…The runoff prediction model is established by combining the success-history adaptive differential evolution algorithm for linear population size reduction (L-SHADE) and simple recurrent unit (SRU). …”
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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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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

“…Results: The evaluation results showed that more than 90 % of specialists had a positive attitude towards application effectiveness. …”
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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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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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