Illustration of model compartment links. حسب Yousef AbuHour (17536686)

"…Additionally, we analyze the reproduction number’s sensitivity and explore the proposed discrete system’s local and global stability. The model was simulated and analyzed using Python packages, providing practical solutions to improve cybersecurity in IoT networks. …"

Table 1_Magnetic resonance imaging-based deep learning for predicting subtypes of glioma.docx حسب Zhen Yang (107412)

"…The receiver operating characteristic curve (ROC), area under the curve (AUC) of the ROC were generated in the jupyter notebook tool using python language to evaluate the accuracy of the models in classification and comparing the predictive value of different MRI sequences.…"

Data from: Circadian activity predicts breeding phenology in the Asian burying beetle <i>Nicrophorus nepalensis</i> حسب Hao Chen (20313552)

"…The repository contains all necessary data and code for reproducing the analyses of beetle breeding phenology predictions using circadian activity patterns.…"

GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios حسب Yang Lan (20927512)

"…</p><p dir="ltr">All data are stored in GeoTIFF (.tif) format and can be accessed and processed using ArcGIS, ENVI, R, and Python. Each GeoTIFF file contains grid-based predictions of habitat suitability, with values ranging from 0 to 1. …"

DRLiPS: A Novel Method for Prediction of Druggable RNA-Small Molecule Binding Pockets Using Machine Learning حسب Sowmya Ramaswamy Krishnan (20867198)

Dataset for the Modeling and Bibliometric Analysis of Business plan for Entrepreneurship حسب Shofie Galuh Amanda (22121604)

"…The analysis and visualization were carried out using R Biblioshiny for thematic mapping and trend topics, and Microsoft Excel for main information and annual publication production. For modeling, Python was applied to generate projection analyses of annual scientific production using polynomial regression. …"

Supplementary Material for: The prediction of hematoma growth in acute intracerebral hemorrhage: from 2-dimensional shape to 3-dimensional morphology حسب figshare admin karger (2628495)

"…Amongst all prediction models, the PCM presented the highest predictive value for active bleeding. …"

Cathode carbon block material parameters [14]. حسب Chenglong Gong (20629836)

"…A random aggregate model was implemented in Python and imported into finite element software to simulate sodium diffusion using Fick’s second law. …"

Sodium concentration distribution cloud map. حسب Chenglong Gong (20629836)

"…A random aggregate model was implemented in Python and imported into finite element software to simulate sodium diffusion using Fick’s second law. …"

Sodium binding coefficient R. حسب Chenglong Gong (20629836)

"…A random aggregate model was implemented in Python and imported into finite element software to simulate sodium diffusion using Fick’s second law. …"

Data Sheet 1_Predicting the prognosis of patients with sudden sensorineural hearing loss by analyzing the audiometric curve of the unaffected ear.zip حسب Xuan Sun (619836)

Experimental Sensor Data from Vehicles for Dynamic Vehicle Models حسب János Kontos (20463344)

"…</p><p><br></p><p dir="ltr">The data is stored in Apache Parquet format that can be processed via Pandas library in Python.</p><p><br></p><p dir="ltr">For more information please check our article:</p><p dir="ltr">Sensitivity Analysis of Long Short-Term Memory-based Neural Network Model for Vehicle Yaw Rate Prediction @MPDI Sensors</p>…"

Image 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.tif حسب Xuehui Fan (10762662)

"…This study aims to analyze the treatment preferences of outpatient rehabilitation patients by using data and a grading tool to establish predictive models. The goal is to improve patient visit efficiency and optimize resource allocation through these predictive models.…"

Iterative Methods for Vecchia-Laplace Approximations for Latent Gaussian Process Models حسب Pascal Kündig (19824557)

"…<p>Latent Gaussian process (GP) models are flexible probabilistic nonparametric function models. …"

Dataset for the Modeling and Bibliometric Analysis of E-business in Entrepreneurship (1997–2024) حسب Aggie Moses Zeuse (21460466)

"…These include a summary of Main Information (PNG), a graph of the Annual Scientific Production (PNG), a Thematic Map (PNG) illustrating core research themes, and an analysis of Trend Topics (PNG). For the modeling component, a predictive analysis was conducted using Python to forecast future publication volumes. …"

A Hybrid Ensemble-Based Parallel Learning Framework for Multi-Omics Data Integration and Cancer Subtype Classification حسب Mohammed Nasser Al-Andoli (21431681)

Data Sheet 7_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

"…This study aims to analyze the treatment preferences of outpatient rehabilitation patients by using data and a grading tool to establish predictive models. The goal is to improve patient visit efficiency and optimize resource allocation through these predictive models.…"

Data Sheet 2_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

"…This study aims to analyze the treatment preferences of outpatient rehabilitation patients by using data and a grading tool to establish predictive models. The goal is to improve patient visit efficiency and optimize resource allocation through these predictive models.…"

Data Sheet 9_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.xlsx حسب Xuehui Fan (10762662)

"…This study aims to analyze the treatment preferences of outpatient rehabilitation patients by using data and a grading tool to establish predictive models. The goal is to improve patient visit efficiency and optimize resource allocation through these predictive models.…"

Data Sheet 5_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

"…This study aims to analyze the treatment preferences of outpatient rehabilitation patients by using data and a grading tool to establish predictive models. The goal is to improve patient visit efficiency and optimize resource allocation through these predictive models.…"