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103
datasets available to search
ShareScore release 0.9.0
Dataset results
103 results for “regression modeling”
Factors Associated with Scientific Production Citations in Dentistry: Zero-inflated Negative Binomial Regression and Hurdle Modelling
<p><strong>Abstracto:</strong> La literatura científica mundial en odontología ha mostrado importantes avances en este campo, con importantes contribuciones que van desde el análisis de los aspectos epidemiológicos básicos de la prevención hasta resultados especializados en el campo de los tratamientos dentales. La presente investigación tiene como objetivo analizar el estado actual de la literatura científica sobre odontología alojada en la base de datos Web of Science. La metodología incluye dos fases en el análisis de artículos y revisiones indexadas en todas las áreas temáticas. Durante la primera fase, se analizan las siguientes variables: la producción científica por parte del editor, la evolución de la producción científica publicada por los editores, los factores asociados al impacto de la producción científica y la modelización del impacto de la producción científica en odontología. Durante la segunda fase, se analizan asociaciones, evoluciones y tendencias en el uso de palabras clave principales en la literatura científica en odontología. En conclusión, el estudio muestra que los temas más estudiados incluyen la asociación de la educación dental y el plan de estudios, la asociación de la odontología pediátrica con la salud oral y el cuidado dental. Los hallazgos muestran que también destacan temas enfatizados más recientemente, como la odontología basada en la evidencia, la pandemia, el control de infecciones y la endodoncia, así como la necesidad de futuras investigaciones para ampliar el conocimiento actual basado en temas emergentes en la literatura científica sobre odontología.</p>
Unpacking the "black box": improving ecological interpretation of regression based models
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Hyperspectral reflectance-based partial least squares regression models for predicting cotton leaf physiological traits
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Data for: A new threshold selection method for species distribution models with presence-only data: extracting the mutation point of the P/E curve by threshold regression
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Data for: Accurate sequence-to-affinity models for SH2 domains from multi-round peptide binding assays coupled with free-energy regression
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Data for: Leveraging spatio-temporal genomic breeding value estimates of dry matter yield and herbage quality in ryegrass via random regression models
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Supplementary Materials include results of simulation experiments to investigate the impact of phylogenetic regression with model violations.
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Data from: Improving performance of hurdle models using rare-event weighted logistic regression: An application to maternal mortality data
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Data for "Function Space Optimization: A symbolic regression method for estimating parameter transfer functions for hydrological models"
<p>This repository contains all geo-physical catchment properties used in the publication "Function Space Optimization: A symbolic regression method for estimating parameter transfer functions for hydrological models".</p>
Imbalanced regressive neural network model for whistler-mode hiss waves: spatial and temporal evolution
<p>This dataset contains the whistler-mode hiss waves obtained from the Van Allen Probes. It is accompanied by the manuscript "<span>Imbalanced regressive neural network model for whistler-mode hiss waves: spatial and temporal evolution". </span></p>
Multivariate Ordinary Least Squares (OLS) regression-based Seismic Hazard Model Data
<p>This dataset includes earthquake parameters, slab geometry, gravity anomalies, and fault proximities used for seismic hazard modeling in the Makran Subduction Zone (MSZ). Supplementary Table S1 contains earthquake data (location, depth, magnitude), slab properties (depth, dip, thickness, strike), and distances to key faults. Supplementary Table S2 provides intraslab seismicity, slab geometry, trench distances, and gravity data. The data are sourced from the USGS Earthquake Catalog, IRIS, Slab-2 model, GMRT, and other geophysical models.</p>
Dataset for "Modeling Cell Populations Measured By Flow Cytometry With Covariates Using Sparse Mixture of Regressions" in the Annals of Applied Statistics
<p>This is the dataset to be used for the paper in the Annals of Applied Statistics titled:</p> <p><strong>"Modeling Cell Populations Measured By Flow Cytometry With Covariates Using Sparse Mixture of Regressions"</strong></p> <p>Download, unzip and place in the ./<strong>paper-data</strong> directory in the R package repository <a href="https://github.com/sangwon-hyun/flowmix">https://github.com/sangwon-hyun/flowmix</a>. Then, run the code in <strong>./paper-code</strong> to produce the figures and tables.</p>
Compound data sets for support vector machine and regression modeling
<p>Provided are compound data sets used for support vector machine and support vector regression modeling and associated information.</p>
Intravoxel incoherent motion model of diffusion weighted imaging and diffusion kurtosis imaging in differentiating of local colorectal cancer recurrence from scar/fibrosis tissue by multivariate logistic regression analysis
<p>We uploaded mean of diffusion coefficient (MD) and mean of diffusional Kurtosis values of 56 patients related to the manuscript: Fusco, Roberta, Vincenza Granata, Mario Sansone, Robert Grimm, Paolo Delrio, Daniela Rega, Fabiana Tatangelo, Antonio Avallone, Nicola Raiano, Giuseppe Totaro, Vincenzo Cerciello, Biagio Pecori, and Antonella Petrillo. 2020. "Intravoxel Incoherent Motion Model of Diffusion Weighted Imaging and Diffusion Kurtosis Imaging in Differentiating of Local Colorectal Cancer Recurrence from Scar/Fibrosis Tissue by Multivariate Logistic Regression Analysis" Applied Sciences 10, no. 23: 8609. https://doi.org/10.3390/app10238609</p>
Predicting Postoperative Pulmonary Infection in Elderly Patients Undergoing Major Surgery: a Study Based on Logistic Regression and Machine Learning Models
ClinicalTrials.gov study NCT06491459. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: A comparison of regression methods for model selection in individual-based landscape genetic analysis
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Code from: Testing for normality in regression models: mistakes abound (but may not matter)
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Datasets used for Multi-omics integration using Deep Learning and other state-of-the-art regression models
<p>This repository link contains the LIHC files that were downloaded using TCGA Assembler 2 and used in the publication for benchmarking DL and other state-of-the-art regression models.</p> <p>The contents are as follows.</p> <p>Gene level CNA , filename= "<a href="https://zenodo.org/api/files/15943ba8-5f3d-4397-8eb2-98ed85693b79/LIHC__genome_wide_snp_6__GeneLevelCNA.txt">LIHC__genome_wide_snp_6__GeneLevelCNA.txt</a>"</p> <p>DNA Methylation data around 1500 bp around TSS (450K) , filename= "<a href="https://zenodo.org/api/files/15943ba8-5f3d-4397-8eb2-98ed85693b79/LIHC_Methylation450__SingleValue__TSS1500__Both.txt">LIHC_Methylation450__SingleValue__TSS1500__Both.tx</a>t"</p> <p>RNASeq data, filename= "<a href="https://zenodo.org/api/files/15943ba8-5f3d-4397-8eb2-98ed85693b79/LIHC_RNASeq__illuminahiseq_rnaseqv2__GeneExp.txt">LIHC_RNASeq__illuminahiseq_rnaseqv2__GeneExp.txt</a>"</p>
Regression committee machine and petrophysical model jointly driven parameter reservoirs prediction from wireline logs for tight sandstone
<pre>This data comes from this study: "Regression committee machine and petrophysical model jointly driven parameter reservoirs prediction from wireline logs for tight sandstone". It is the intelligent prediction result of porosity, permeability and water saturation of two wells in the Ordos Basin, China</pre>
Data from: Improving estimates of environmental change using multilevel regression models of Ellenberg indicator values
Ellenberg indicator values (EIVs) are a widely used metric in plant ecology comprising a semi-quantitative description of species' ecological requirements. Typically, point estimates of mean EIV scores are compared to infer differences in the environmental conditions structuring plant communities – particularly in resurvey studies with no historical environmental data available. However, the use of point estimates as a basis for inference does not take into account variance among species EIVs within sampled plots, and gives equal weighting to means calculated from sites with differing numbers of species. We present a set of multilevel models – fitted with and without group-level predictors – to improve precision and accuracy of site mean EIV scores, and to provide more reliable inference on changing environmental conditions over spatial and temporal gradients in re-visitation studies. We compare multilevel model performance to GLMM's fitted to point estimates of site mean EIVs. We also test the reliability of this method to improve inferences with incomplete species lists in some or all sample sites. Hierarchical modelling led to more accurate and precise estimates of site-level differences in mean EIV scores between time-periods, particularly for datasets with incomplete records of species occurrence. They also revealed directional environmental change within ecological habitat types, which estimates from GLMM's were inadequate to detect. Multilevel models also highlighted a prominent role of hydrological differences as a driver of community change in our case study, which traditional use of EIVs failed to reveal. We have demonstrated that multilevel modelling of EIVs allows for a nuanced estimation of environmental change underlying ecological communities from plant assemblage data, leading to a better understanding of temporal dynamics of ecosystems. Further, the ability of these methods to perform well with missing data should increase the total set of historical data which can be used to this end.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.