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General ML benchmarks, tabular data, AutoML, recommendation systems, anomaly detection, evaluation suites
170,662 datasets
40 studies on machine learning models for predicting adverse outcomes in aortic dissection were systematically reviewed and meta-analyzed. The analysis, registered with PROSPERO, synthesized performance metrics like C-statistics and assessed risk of bias using PROBAST. It covers outcomes including early mortality, long-term mortality, and acute kidney injury.
40 studies on machine learning models for aortic dissection risk prediction were systematically reviewed and meta-analyzed. The analysis, conducted by Yijun Mao, synthesized performance metrics like pooled C-statistics for outcomes including early mortality and acute kidney injury.
40 studies from a systematic review up to September 2025 synthesize performance metrics for machine learning models predicting aortic dissection outcomes. The dataset includes pooled C-statistics for outcomes like early mortality, long-term mortality, and acute kidney injury, with performance metrics and bias assessments. It was compiled by author Yijun Mao following PRISMA and CHARMS guidelines.
A systematic review and meta-analysis of 40 studies evaluating machine learning models for predicting adverse outcomes in aortic dissection. The analysis, conducted by Yijun Mao, synthesized performance metrics like C-statistics (AUC) for outcomes including early mortality, long-term mortality, and acute kidney injury.
A systematic review and meta-analysis of 40 studies evaluating machine learning models for predicting adverse outcomes in aortic dissection, published up to September 2025. The analysis, conducted by Yijun Mao and following PRISMA guidelines, synthesized performance metrics like C-statistics for outcomes including early mortality and acute kidney injury. The document was last updated on March 26, 2026.
Yijun Mao's systematic review synthesizes performance metrics from 40 studies on machine learning models for predicting adverse outcomes in aortic dissection. The meta-analysis reports pooled C-statistics, such as 0.891 for early mortality prediction, and assesses study quality using PROBAST and TRIPOD guidelines.
Forty studies were systematically reviewed and meta-analyzed to evaluate machine learning models for predicting adverse outcomes in aortic dissection. The analysis synthesized performance metrics like C-statistics for outcomes including early mortality, long-term mortality, and acute kidney injury. It was conducted by Yijun Mao following PRISMA guidelines, with searches up to September 30, 2025.
Statistics from 2021 onward for services provided by police inspections in the Barranquilla District. The dataset includes columns for TIPO DE SERVICIO, CANTIDAD, AÑO, MES, and PERIODO. It is hosted on the Socrata platform by www.datos.gov.co.
9,850 plot-level observations from six major coffee-producing counties in Kenya form the basis for this comparative model evaluation. The dataset, created by Maurice Wanyonyi and last updated in April 2026, compares Bayesian hierarchical inference and supervised machine learning approaches for predicting coffee rust incidence. It focuses on microclimatic moisture variables like leaf wetness duration and relative humidity as key predictors.
The Department of Energy, Environment and Climate Action (DEECA) provides this geospatial dataset of office and depot locations for DEECA, Parks Victoria, and Agriculture Victoria. The data is available in multiple GIS formats including SHP, DWG, and GDB, and was last updated on May 12, 2026. It is published under a Creative Commons Attribution 4.0 license.
A structured inventory of information assets for the Municipal Mayor's Office of Puerres. The dataset includes 20 columns describing administrative processes, document formats, responsible parties, and archival details. It was published on the Colombian open data portal and last updated on 2026-05-18.
Corantioquia's jurisdiction contains a registry of discharges to soil from water resource users. The dataset includes columns for basin, discharge type, flow rate, and treatment methods. It is published by www.datos.gov.co and was last updated on 2026-05-18.
Data from 2019 and 2020 on disbursements from the Findeter rediscount program, organized by department in Colombia. The dataset is hosted by the Colombian government's open data portal, datos.gov.co, and was last updated in May 2026. It includes columns for department, sector, disbursement amount, fiscal year (Vigencia), and location.
Facatativá, Colombia's municipal government provides an inventory of desktop and laptop computers installed in its central administrative building. The dataset includes columns for hardware specifications like processor, RAM, operating system, and model. It was last updated on 2026-05-18 via the datos.gov.co platform.
Non-fetal death records for the department of Caldas, Colombia, starting from the 2010 period. The data includes columns for municipality of residence, age, sex, cause of death, and month of death. It is hosted by the Colombian open data portal www.datos.gov.co and was last updated on 2026-05-18.
Operational indicators from a Balanced Scorecard (Cuadro de Mando Integral or CMI) management system. The dataset includes columns for goals, indicators, descriptions, execution status, and result analysis. It originates from the Colombian open data portal www.datos.gov.co and was last updated on 2026-05-18.
257.6 KB of experimental data supporting a 2024 journal article on evaluating membrane behavior with ethanol-water mixtures and wine. The dataset, authored by Andrea Versari and colleagues, is available in XLSX format under a CC-BY-4.0 license. It was last updated on the figshare platform in May 2026.
Monthly updated spatial data from the NSW Rural Fire Service, including archived fire data from the current fire year. The dataset contains fire history, bush fire prone land, hazard reduction advice, and administrative boundaries for RFS stations and districts. It is produced by the NSW Government and supplied to Emergency Service Agencies.
Chu published results from a PINN-assisted hierarchical resolution adaptive refinement algorithm used in MICP numerical simulation on figshare. The dataset is 1.5 GB in size and consists of VTK format files. It was last updated on 2026-05-25.
Ran Zhou provides a 158.0 KB collection of input data files in CSV and XLSX formats, last updated in May 2026. The dataset includes the USL dataset, fNANI and fNAPI data, and INCI data. A README file in the associated code repository provides instructions for reproducing results.