Next Generation Visual Analytics

Next Generation Visual Analytics is an interactive, user-friendly biomedical data dashboard designed to simplify complex data analysis and visualization tasks for biomedical research. The platform integrates comprehensive tools for data preprocessing, exploratory data analysis, visualization, dimensionality reduction, machine learning modeling, and both medical and natural image analysis. Users can efficiently manage missing values, detect outliers, and transform datasets using intuitive graphical interfaces. The dashboard supports various visualization techniques, including scatter plots, heatmaps, violin plots, and dimensionality reduction methods such as PCA, t-SNE, and UMAP, enhancing interpretability of large datasets. Advanced users can leverage built-in supervised machine learning models like Logistic Regression, Random Forest, and Support Vector Machines, complete with automatic feature selection, model evaluation through cross-validation, and performance visualization tools. Additionally, the integrated medical imaging module allows volumetric data processing and organ segmentation using pre-trained deep learning models, while the natural image analysis component includes standard computer vision tasks like grayscale conversion, edge detection, and histogram equalization. Finally, the dashboard also has an AI assistant powered by Llama 4, enabling users to ask questions about their data and receive context-aware answers about biomedical analysis. Next Generation Visual Analytics significantly streamlines data-driven biomedical research, promoting accessibility and efficiency.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-02
DOI
https://doi.org/10.5281/zenodo.15380211
Primary Topic
Gout, Hyperuricemia, Uric Acid
Type
article
Field-Weighted Citation Impact
0.00
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article

Next Generation Visual Analytics

Zenodo (CERN European Organization for Nuclear Research)
Gout, Hyperuricemia, Uric Acid
article

Next Generation Visual Analytics

article en

Abstract

Next Generation Visual Analytics is an interactive, user-friendly biomedical data dashboard designed to simplify complex data analysis and visualization tasks for biomedical research. The platform integrates comprehensive tools for data preprocessing, exploratory data analysis, visualization, dimensionality reduction, machine learning modeling, and both medical and natural image analysis. Users can efficiently manage missing values, detect outliers, and transform datasets using intuitive graphical interfaces. The dashboard supports various visualization techniques, including scatter plots, heatmaps, violin plots, and dimensionality reduction methods such as PCA, t-SNE, and UMAP, enhancing interpretability of large datasets. Advanced users can leverage built-in supervised machine learning models like Logistic Regression, Random Forest, and Support Vector Machines, complete with automatic feature selection, model evaluation through cross-validation, and performance visualization tools. Additionally, the integrated medical imaging module allows volumetric data processing and organ segmentation using pre-trained deep learning models, while the natural image analysis component includes standard computer vision tasks like grayscale conversion, edge detection, and histogram equalization. Finally, the dashboard also has an AI assistant powered by Llama 4, enabling users to ask questions about their data and receive context-aware answers about biomedical analysis. Next Generation Visual Analytics significantly streamlines data-driven biomedical research, promoting accessibility and efficiency.

Zenodo (CERN European Organization for Nuclear Research)
Georgia Institute of Technology (US), Emory University (US)
Openalex Percentile: Top 45%
Gout, Hyperuricemia, Uric Acid
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