Machine learning for detection of diffusion abnormalities-related respiratory changes among normal, overweight, and obese individuals based on BMI and pulmonary ventilation paramet... by Xin-Yue Song, Xin-Peng Xie, Wen-Jing Xu, Yu-Jia Cao, Bin-Miao Liang

“…Additionally, we performed feature importance analysis using shapley additive explanations (SHAP) and permutation importance to evaluate the contribution of individual parameters to the classification process. Results Our findings revealed that individuals in the DA group demonstrated lower PEF and DLCO than their DN counterparts. …”
Get full text

Machine learning-based real-time prediction of duodenal stump leakage from gastrectomy in gastric cancer patients by Jae Hun Chung, Jae Hun Chung, Jae Hun Chung, Yushin Kim, Dongjun Lee, Dongwon Lim, Dongwon Lim, Dongwon Lim, Sun-Hwi Hwang, Sun-Hwi Hwang, Sun-Hwi Hwang, Si-Hak Lee, Si-Hak Lee, Si-Hak Lee, Woohwan Jung

“…Six ML algorithms were evaluated: Logistic Regression (LR), K-nearest neighbors (KNN), Support Vector Machine (SVM), Random Forest (RF), Extreme Gradient Boosting (XGB), and Neural Network (NN). …”
Get full text

Predicting specific wear rate of laser powder bed fusion AlSi10Mg parts at elevated temperatures using machine learning regression algorithm: Unveiling of microstructural morpholog... by Vijaykumar S. Jatti, R. Murali Krishnan, A. Saiyathibrahim, V. Preethi, Suganya Priyadharshini G, Abhinav Kumar, Shubham Sharma, Saiful Islam, Dražan Kozak, Jasmina Lozanovic

“…However, to accurately predict the wear rate at high temperatures, six different machine learning regression algorithms were used, namely Support Vector Machine (SVM), Linear Regression (LR), Random Forest Regression (RFR), Gaussian Process Regression (GPR), XGBoost regression (XGB) and Decision Tree (DT). …”
Get full text

Improved estimation of forage nitrogen in alpine grassland by integrating Sentinel-2 and SIF data by Yongkang Zhang, Jinlong Gao, Dongmei Zhang, Tiangang Liang, Zhiwei Wang, Xuanfan Zhang, Zhanping Ma, Jinhuan Yang

“…In this study, we integrates SIF products from TanSat and Orbiting Carbon Observatory-2 (OCO-2) satellites, Sentinel-2 Multi-Spectral Instrument (MSI) data with derived vegetation indices, and field observations across phenological stages (green-up stage, vigorous growth stage, and senescence stage) in northeastern Tibetan Plateau alpine grasslands to develop support vector machine (SVM), gaussian process regression (GPR), and artificial neural network (ANN) models for regional-scale forage nitrogen estimation. …”
Get full text

An optimized approach for predicting water quality features and a performance evaluation for mapping surface water potential zones based on Discriminant Analysis (DA), Geographical... by Abhijeet Das

“…Again, this research used a strong methodology by incorporating Machine learning (ML) algorithms, such as: Artificial Neural Network (ANN), Gaussian Process Regression (GPR), Support Vector Machine (SVM), and Linear Regression Model (LRM), were applied to forecast and confirm the quality of the water. …”
Get full text

Leveraging moisture elimination and hybrid deep learning models for soil organic carbon mapping with multi-modal remote sensing data by Yilin Bao, Xiangtian Meng, Weimin Ruan, Huanjun Liu, Mingchang Wang, Abdul Mounem Mouazen

“…The MCCL model was compared to other machine learning and deep learning models, including LSTM, Random Forest (RF), CNN, Artificial Neural Network (ANN), Support Vector Machine (SVM) and partial least squares regression (PLSR). …”
Get full text

Comparative analysis of Egypt's malaria elimination strategies and implementation science: Pathways to achieve malaria-free status for other African countries. by Chukwuka Elendu, Dependable C Amaechi, Rhoda C Elendu, Sehajmeet Kaur Saggi, Tochi C Elendu, Emmanuel C Amaechi, Ijeoma D Elendu, Kanishk Dang, Opeyemi P Amosu, Omoyelemi F Idowu, Toluwanimi S Oseni

“…Economic evaluations and process analyses provided additional insights into cost-effectiveness and operational efficiency.…”
Get full text

Screening and identification of protein 29 of Echinococcus granulosus interacting molecules by Zailing Shang, Fei Qiao, Yaning Li, Xuelin Ma, Mingxia Wang, Wenji Yang, Tianyu He, Haixia Ma, Yana Wang, Yana Wang

“…However, the function of Eg.P29 remains unknown. During the process life, protein is commonly with other proteins to form a complex network of interactions to play the function. …”
Get full text

Artificial intelligence in vaccine research and development: an umbrella review by Rabie Adel El Arab, May Alkhunaizi, May Alkhunaizi, Yousef N. Alhashem, Alissar Al Khatib, Munirah Bubsheet, Salwa Hassanein, Salwa Hassanein

“…Quality assessments were performed using the ROBIS and AMSTAR 2 tools to evaluate risk of bias and methodological rigor.ResultsAmong the 27 reviews, traditional machine learning approaches—random forests, support vector machines, gradient boosting, and logistic regression—dominated tasks from antigen discovery and epitope prediction to supply‑chain optimization. …”
Get full text

High-Efficiency Multi-Standard Polynomial Multiplication Accelerator on RISC-V SoC for Post-Quantum Cryptography by Duc-Thuan Dam, Trong-Hung Nguyen, Thai-Ha Tran, Duc-Hung Le, Trong-Thuc Hoang, Cong-Kha Pham

“…With a unified design, the accelerator performs NTT, inverse NTT (INTT), point-wise multiplication (PWM), and matrix-vector polynomial multiplication. Secondly, we propose a compact, configurable reordering unit for effective coefficient processing in high-parallelism. …”
Get full text

Suppression of METTL3 expression attenuated matrix stiffness-induced vaginal fibroblast-to-myofibroblast differentiation and abnormal modulation of the extracellular matrix in pelv... by Xiuqi Wang, Tao Guo, Xiaogang Li, Zhao Tian, Linru Fu, Zhijing Sun, Jinjiao Li

“…Conversely, METTL3 overexpression significantly promoted the process of increased proliferation ability, increased α-SMA expression, decreased ratio of collagen I/III and decreased TIMP1 and TIMP2 expression in the soft matrix (P <0.05). …”
Get full text

Hyperspectral and LiDAR space-borne data for assessing mountain forest volume and biomass by Rodolfo Ceriani, Sebastian Brocco, Monica Pepe, Silvio Oggioni, Giorgio Vacchiano, Renzo Motta, Roberta Berretti, Davide Ascoli, Matteo Garbarino, Donato Morresi, Francesco Bassi, Francesco Fava

“…We compared EMIT with Sentinel-2 (S2) multispectral data as model inputs, with and without GEDI data integration, using five Machine Learning (ML) algorithms: Partial Least Squares Regression (PLSR), Boosted Regression Trees (BRT), Support Vector Machines (SVM), Artificial Neural Networks (ANN), and Gaussian Process Regression (GPR). …”
Get full text

Manufacturing of CD19 Specific CAR T-Cells and Evaluation of their Functional Activity in Vitro by AV Petukhov, VA Markova, DV Motorin, AK Titov, NS Belozerova, PM Gershovich, AV Karabel’skii, RA Ivanov, EK Zaikova, EYu Smirnov, PA Butylin, AYu Zaritskey

“…Human T-lymphocytes were transduced by the lentiviral vector containing anti-CD19-CAR, RIAD, and GFP genes. …”
Get full text

Predicting climate-driven shift of the East Mediterranean endemic Cynara cornigera Lindl by Heba Bedair, Heba Bedair, Yehia Hazzazi, Asmaa Abo Hatab, Marwa Waseem A. Halmy, Mohammed A. Dakhil, Mohammed A. Dakhil, Mubaraka S. Alghariani, Mubaraka S. Alghariani, Mari Sumayli, A. El-Shabasy, Mohamed M. El-Khalafy

“…Our analysis involved inclusion of bioclimatic variables, in the SDM modeling process that incorporated five algorithms: generalized linear model (GLM), Random Forest (RF), Boosted Regression Trees (BRT), Support Vector Machines (SVM), and Generalized Additive Model (GAM).Results and discussionThe ensemble model obtained high accuracy and performance model outcomes with a mean AUC of 0.95 and TSS of 0.85 for the overall model. …”
Get full text

Identification of an unmanned aerial vehicle pilot-operator dynamics model under stochastic conditions by C. І. Осадчий, А. М. Івлієв, С. Ф. Колісніченко, Г. С. Тимошенко

“…An additive mixture of a vector random useful signals and random noises is allowed at the object output. …”
Get full text

Alteration of mitochondrial function in arthropods during arboviruses infection: a review of the literature by María E. Santana-Román, Santos Ramírez-Carreto, Paola Maycotte, Victoria Pando-Robles

“…Arthropods serve as vectors for numerous arboviruses responsible for diseases worldwide. …”
Get full text

Implementation and Evaluation of Machine Learning Algorithms in Ball Bearing Fault Detection by Stepanić Pavle, Dučić Nedeljko, Vidaković Jelena, Baralić Jelena, Popović Marko

“…For each recorded vibration signal, a feature extraction was performed by digital processing in the time domain. The following ML algorithms were used to develop the classifier: K-nearest neighbor (KNN) and support vector machine (SVM) as well as improved versions of the aforementioned algorithms. …”
Get full text

Machine learning‐guided plasticity model in refractory high‐entropy alloys by Shang Zhao, Jinshan Li, Weijie Liao, Ruihao Yuan

“…Through feature selection techniques, a critical subset of features is identified, enabling a support vector classification model to achieve 96% prediction accuracy. …”
Get full text

Unitarity bounds and basis transformations in SMEFT: An analysis of Warsaw and SILH bases by Qing-Hong Cao, Yandong Liu, Shu-Run Yuan

“…We employ a coupled channel analysis to scrutinize scattering processes involving vector bosons and fermions. We conduct a comprehensive investigation into the transformation of unitarity bounds under changes in the operator basis. …”
Get full text

Automated image-based condition assessment of the built environment: A state-of-the-art investigation of damage characteristics and detection requirements by Leila Farahzadi, Ibrahim Odeh, Mahdi Kioumarsi, Behrouz Shafei

“…For the automated detection, localization, and measurement of damage, various convolutional neural network, support vector machine, and classification-based methods were examined, including their advantages and limitations. …”
Get full text