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General ML benchmarks, tabular data, AutoML, recommendation systems, anomaly detection, evaluation suites
141,875 datasets
103,693 young adults with normal baseline fasting plasma glucose were tracked for incident diabetes over a median follow-up of 2.99 years. The data, sourced from the Rich Healthcare Group health check-up database in China, was analyzed using Cox regression and machine learning models like XGBoost. SHAP analysis identified BMI as the most influential predictor, revealing a nonlinear risk increase beyond approximately 28 kg/m².
A 5.5 KB dataset published on figshare by Hao Yuan on 2026-05-27. It contains performance evaluation results for a proposed blockchain-based multi-authority hierarchical attribute-based encryption scheme designed for the Internet of Medical Things. The description indicates the data was generated from large-scale testing in a 100-node Hyperledger Fabric environment.
Performance evaluation data for a blockchain-based multi-authority hierarchical attribute-based encryption scheme designed for the Internet of Medical Things. The dataset likely contains computational and storage overhead metrics for the proposed CP-ABE algorithm, along with consensus latency and key update propagation delay results from a 100-node Hyperledger Fabric test. Author Hao Yuan published the data on figshare in May 2026 under a CC-BY-4.0 license.
5.5 KB of tabular data compares the computational and storage overhead of a proposed blockchain-based encryption scheme for the Internet of Medical Things. The dataset, authored by Hao Yuan and last updated in May 2026, supports a paper proposing a multi-authority hierarchical attribute-based encryption method. Performance metrics include consensus latency of approximately 280 ms and key update propagation delay of 1.52 seconds from tests on a 100-node Hyperledger Fabric environment.
A comparative study of Ciphertext-Policy Attribute-Based Encryption (CP-ABE) schemes for the Internet of Medical Things (IoMT). The dataset, authored by Hao Yuan and last updated in May 2026, likely contains performance metrics from a 100-node Hyperledger Fabric test, including consensus latency and key update propagation delay.
A dataset comparing the computational and storage overhead of a proposed Ciphertext-Policy Attribute-Based Encryption (CP-ABE) scheme designed for the Internet of Medical Things (IoMT). The data was generated by Hao Yuan and uploaded to figshare on 2026-05-27. Performance evaluation indicates the CP-ABE algorithm in this scheme outperforms existing solutions in computational overhead.
A dataset of cloud computing operational records for research in sustainable resource management, authored by Kalaiselvi S and last updated in May 2026. The 32.1 MB collection in CSV format captures interactions between workload demand, resource utilization, energy consumption, and carbon emission indicators. It is intended for developing machine learning and optimization models aimed at reducing environmental impact while maintaining service quality.
A 32.1 MB dataset of cloud computing operational records, published on figshare by Kalaiselvi S under a CC-BY-4.0 license and last updated on 2026-05-29. It captures interactions between workload demand, resource utilization, energy consumption, and carbon emission indicators for research in sustainable computing.
A collection of cloud computing operational records for research in sustainable resource management. The dataset was authored by Kalaiselvi S and last updated on May 29, 2026. It is 32.1 MB in size and is provided in CSV format under a CC-BY-4.0 license.
A cross-sectional study of 143 community-dwelling older adults aged 60 years and above with chronic diseases. The dataset includes 24-hour movement behaviors measured by accelerometer and psychological distress scores from the Kessler K10 scale, analyzed using compositional isotemporal substitution methods. The data was published by Hanchen Tian on figshare in May 2026.
The dataset was collated from sources including the approved programs collection, project data reporting standard, and assurance oversight activities. Information was collected between July and November 2025, with all data validated with agencies by 3 November 2025. This report and its accompanying dataset is published annually by the Digital Transformation Agency.
A systematic review and meta-analysis of observational studies evaluating the association between semaglutide use and nonarteritic anterior ischemic optic neuropathy (NAION) risk in patients with type 2 diabetes. The dataset includes pooled hazard ratios and confidence intervals from studies published between January 2023 and November 2025. It was authored by Jędrzej Chrzanowski and published on figshare in May 2026.
A dataset used to develop and validate a machine learning model for identifying advanced Parkinson's disease. It contains retrospective data from 536 patients in a discovery cohort and 80 patients in an external validation cohort. The model uses six routine blood biomarkers selected by LASSO and Random Forest algorithms.
915 TBI patients from the MIMIC-IV database and 317 from the eICU-CRD database were used to develop a machine learning model for predicting incident delirium. The Random Forest model achieved an internal AUC of 0.819 and an external AUC of 0.706. The study, authored by Cheng Li and last updated in May 2026, includes predictors like Glasgow Coma Scale and invasive ventilation, with SHAP analysis for interpretability.
Data from 3,357 physically inactive adults in the Korea National Health and Nutrition Examination Survey (KNHANES, 2007–2012) was used to develop a predictive model. The XGBoost model was validated internally with KNHANES 2011–2012 data and externally with the U.S. NHANES dataset. The dataset, authored by Yuwen Shangguan, is associated with a study published on figshare.
Monthly global Principal Components Analysis (PCA) coefficients for land surface emissivity at a 0.05 degree (~5 kilometer) resolution. This NASA MEaSUREs dataset, derived from Combined ASTER and MODIS Emissivity for Land (CAMEL) data, includes variables for PCA coefficients, laboratory version, snow fraction, and quality flags. The dataset version referenced (CAM5K30CF.001) was decommissioned in March 2019, with users directed to an updated version.
NASA's CAMEL dataset provides monthly land surface emissivity uncertainty at a 0.05-degree (~5 kilometer) resolution. The data quantifies three independent components of variability—algorithm, spatial, and temporal—for 13 spectral hinge points across each latitude-longitude point. This product is part of the MEaSUREs program and corresponds to the CAM5K30EM emissivity values.
Edwin A. Solares presents a dataset of 246 high-quality ultrasound images from 44 red abalone (Haliotis rufescens) individuals, used to benchmark machine learning models for non-invasive sex determination. The dataset was used to evaluate seven convolutional neural network architectures, with YOLOv8 achieving the highest test accuracy of 85.7%. The dataset was last updated on 2026-05-18.
China and the Philippines were impacted by a tropical storm from September 16 to 19, 2025, with the storm center located near latitude 22.8 and longitude 115.4. The dataset is produced by the World Food Programme's Automated Disaster Analysis and Mapping (ADAM) system for humanitarian emergency response. It was last updated on May 21, 2026.
WFP's ADAM system captured geospatial data for a Category 1 storm near latitude 24.0, longitude -113.7 in early September 2025. The dataset, provided by the World Food Programme's Automated Disaster Analysis and Mapping system, includes shapefile and CSV formats for analysis. It was last updated in May 2026.