Identification of HER2-over-expression, HER2-low-expression, and HER2-zero-expression statuses in breast cancer based on 18F-FDG PET/CT radiomics by Xuefeng Hou, Kun Chen, Huiwen Luo, Wengui Xu, Xiaofeng Li

“…Then, four machine learning classifiers, including logistic regression (LR), k-nearest neighbor (KNN), support vector machine (SVM), and random forest (RF), were constructed to identify HER2-over-expression vs. others, HER2-low-expression vs. others, and HER2-zero-expression vs. others. …”
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Theoretical and applied problems of interaction between the international and national legal systems by O. A. Kiseleva

“…In such conditions, it is most important to choose the right vector in improving international law, and not order, law based on normative principles. …”
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AIM2 activation mediated by RIPK1/3-dependent mitochondrial DNA release drives Aβ1−40-Induced retinal pigment epithelium injury by Xiaoxu Huang, Tongqi Li, Guanran Zhang, Jieqiong Chen, Tong Li, Shiqi Yang, Qiyu Bo, Xiaohuan Zhao, Xiaoling Wan, Xinyue Zhu, Bo Yu, Xiaodong Sun, Junran Sun

“…Adeno-associated virus vector 2/2 (AAV2/2)-shAIM2 was constructed to knockdown AIM2 expression in mice RPE cells. …”
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Machine learning for predicting neoadjuvant chemotherapy effectiveness using ultrasound radiomics features and routine clinical data of patients with breast cancer by Pu Zhou, Pu Zhou, Hongyan Qian, Pengfei Zhu, Jiangyuan Ben, Jiangyuan Ben, Guifang Chen, Qiuyi Chen, Lingli Chen, Jia Chen, Ying He, Ying He

“…We compared 10 ML models based on radiomics features: support vector machine (SVM), logistic regression (LR), random forest, extra trees (ET), naïve Bayes (NB), k-nearest neighbor (KNN), multilayer perceptron (MLP), gradient boosting ML (GBM), light GBM (LGBM), and adaptive boost (AB). …”
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Understanding one health challenges in marginalized urban settings: A patient and public involvement (PPI) approach from the CHIP consortium activities across four global cities by Logan Manikam, Darlington David Faijue, Kalpita Shringarpure, Margi Sheth, Pam Factor-Livak, Priti Parikh, Hector Altamirano-Medina, Dewi Nur Aisyah, Radhika Sharma, Hemant Chaturvedi, Kaushik Sarkar, Rajib Dasgupta, Nancy Hiu Lan Leung, Pradeep Kumar Srivastava, Monica Lakhanpaul

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Data fusion-based improvements in empirical regression and machine learning for global daily ∼ 8 km resolution sea surface nitrate estimation and interpretation by Aifen Zhong, Difeng Wang, Fang Gong, Jingjing Huang, Zhuoqi Zheng, Xianqiang He, Qing Zhang, Qiankun Zhu

“…For the machine learning models, seven algorithms, namely, extremely randomized trees (ET), multilayer perceptron (MLP), stacking random forest (SRF), Gaussian process regression (GPR), support vector machine (SVM), gradient boosting decision tree (GBDT), and extreme gradient boosting (XGBoost) algorithms, were tested. …”
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Influences of Sampling Design and Model Selection on Predictions of Chemical Compounds in Petroferric Formations in the Brazilian Amazon by Niriele Bruno Rodrigues, Theresa Rocco Barbosa, Helena Saraiva Koenow Pinheiro, Marcelo Mancini, Quentin D. Read, Joshua Blackstock, Edwin H. Winzeler, David Miller, Phillip R. Owens, Zamir Libohova

“…This highly weathered geological and pedological occurrence makes the site ideal for studying the pedogenetic process of lateralization and the spatial variability of chemical elements. …”
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Association of infection-induced antibody levels with risk of subsequent SARS–COV-2 reinfection among healthcare professionals, Rhode Island, 1 March 2020–17 February 2021 by Jianrong Shi, M. Gayle Gabriel, Monica Epperson, Phil A. Chan, Jefferson M. Jones, Lyle R. Petersen, Melissa Briggs Hagen, Natalie J. Thornburg, Sharon Saydah, Claire M. Midgley

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A double-layer model for improving the estimation of wheat canopy nitrogen content from unmanned aerial vehicle multispectral imagery by Zhen-qi LIAO, Yu-long DAI, Han WANG, Quirine M. KETTERINGS, Jun-sheng LU, Fu-cang ZHANG, Zhi-jun LI, Jun-liang FAN

“…., multiple stepwise regression (MSR), support vector regression (SVR), gradient boosting decision tree (GBDT), Gaussian process regression (GPR), back propagation neural network (BPNN) and radial basis function neural network (RBFNN), were compared for the retrieval of winter wheat LAI, CPP and CNC values, and a double-layer model was proposed for estimating CNC based on LAI and CPP. …”
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Machine learning to identify suitable boundaries for band-pass spectral analysis of dynamic [ $$^{11}$$ 11 C]Ro15-4513 PET scan and voxel-wise parametric map generation by Zeyu Chang, Colm J. McGinnity, Rainer Hinz, Manlin Wang, Joel Dunn, Ruoyang Liu, Mubaraq Yakubu, Paul Marsden, Alexander Hammers

“…Frequency ranges are based on inspection of spectra, prior knowledge of receptor distribution, and blocking studies. The process currently requires the manual selection of frequency ranges based on the data. …”
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Enhanced Multilinear PCA for Efficient Image Analysis and Dimensionality Reduction: Unlocking the Potential of Complex Image Data by Tianyu Sun, Lang He, Xi Fang, Liang Xie

“…The proposed EMPCA algorithm holds promise for reducing image analysis runtimes and advancing rapid image processing techniques.…”
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Water‐to‐Air Imaging: A Recovery Method for the Instantaneous Distorted Image Based on Structured Light and Local Approximate Registration by Bijian Jian, Ting Peng, Xuebo Zhang, Changyong Lin

“…Experimental results show that the proposed algorithm can not only reduce image distortion and improve image visualization, but also has significantly better computational efficiency than other methods, achieving an “end‐to‐end” processing effect.…”
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Migratory phase of Litomosoides sigmodontis filarial infective larvae is associated with pathology and transient increase of S100A9 expressing neutrophils in the lung. by Gregory Karadjian, Frédéric Fercoq, Nicolas Pionnier, Nathaly Vallarino-Lhermitte, Emilie Lefoulon, Adélaïde Nieguitsila, Sabine Specht, Leo M Carlin, Coralie Martin

“…Little is known of the early phase of the parasite life cycle, after the L3 is inoculated in the dermis by the vector and enters the afferent lymphatic vessels and before the moulting processes in the pleural cavity. …”
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Detection of Wood Boring Insects’ Larvae Based on the Acoustic Signal Analysis and the Artificial Intelligence Algorithm by Piotr BILSKI, Piotr BOBIŃSKI, Adam KRAJEWSKI, Piotr WITOMSKI

“…The paper presents an application of signal processing and computational intelligence methods to detect presence of the wood boring insects larvae in the wooden constructions (such as the furniture of buildings). …”
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Usage of hypercomplex numbers in a cryptographic key agreement protocol based on neural networks by Павел Павлович Урбанович, Надежда Павловна Шутько

“…The features of the software implementation of a system simulator based on interacting TРMs are described, and the results of using the developed tool for analysing the dynamics of processes in the system under consideration are presented. …”
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Significance of Machine Learning-Driven Algorithms for Effective Discrimination of DDoS Traffic Within IoT Systems by Mohammed N. Alenezi

“…The performance of the models and data quality improved when emphasizing the impact of feature selection and data pre-processing approaches. Five machine learning models were evaluated by utilizing the Edge-IIoTset dataset: Random Forest (RF), Support Vector Machine (SVM), Long Short-Term Memory (LSTM), and K-Nearest Neighbors (KNN) with multiple K values, and Convolutional Neural Network (CNN). …”
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Designing an intelligent push model for user emotional topics based on dynamic text categorization in social media news dissemination by Jixuan Wang

“…The model initiates data input processing by employing word segmentation and word vector extraction, culminating in the formation of an attention-based bidirectional long short-term memory (ATT-Bi-LSTM) model, which incorporates an attention mechanism for discerning positive and negative emotions. …”
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Probabilistic Analysis of the Auto Tracking Failure by the Mobile Robot Video System by A. A. Lobaty, M. M. Tatur, A. K. Ibrahim

“…The mathematical formulation of the probabilistic analysis problem is based on the processes representation occurring in the system by a vector stochastic differential equation. …”
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Intrusion Detection-Data Security Protection Scheme Based on Particle Swarm-BP Network Algorithm in Cloud Computing Environment by Zhun Wang, Xue Chen

“…Then, by introducing the decision tree algorithm, the overfitting is reduced and the data processing speed of the model is improved, and on this basis, the feature selection is carried out through the “gain rate” optimization method, which reduces the redundant information of the feature vector. …”
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Development of AI-Based Public Safety System with Face Recognition Using CNN and SVM Models in Real-Time by Naila Ratu Alifa, Yana Cahyana, Rahmat Rahmat, Sutan Faisal

“…The methods used include processing facial image datasets, training models using CNN for feature extraction, and SVM for gender classification. …”
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