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Medical imaging (X-ray, CT, MRI), electronic health records, clinical trials, ECG/EEG, pathology
13,087 datasets
Biopsy-confirmed non-diabetic kidney disease was present in 53% of the 1,136 diabetic patients studied. The dataset contains 103 parameters from electronic medical records used to train seven machine learning models, with the best achieving an AUC of 0.841 for detecting NDKD. This resource supports the development of computational diagnostic tools for patients where invasive kidney biopsy is not feasible.
A summary table detailing the size and training/validation/test splits for three datasets used in a medical imaging study. The datasets focus on predicting disease severity in retinopathy of prematurity (ROP) and knee osteoarthritis (OA), and breast density. The 5.5 KB Excel file was authored by Katharina V. Hoebel and last updated in April 2026.
Fulgence Kaboré published a dataset on figshare describing the distribution of patients according to pain location at a baseline time point (M0). The dataset is 5.5 KB in size and is available as an XLS file under a CC-BY-4.0 license. It was last updated on April 24, 2026.
PASD is a 3D MRI dataset for Placenta Accreta Spectrum (PAS) diagnosis. It contains voxel-level lesion masks and case-level diagnostic labels, accompanying a paper published in IEEE Transactions on Image Processing. The dataset was created by ChipYTY and was last updated on 2026-05-13.
Encompassing extracted data from a systematic review and meta-analysis of 18 studies involving 262,468 participants. It examines the association between the Dietary Inflammatory Index (DII) and the incidence and progression of non-alcoholic fatty liver disease (NAFLD). The analysis includes odds ratios, confidence intervals, and results from sensitivity and subgroup analyses.
Durable Medical Equipment suppliers in Colorado are listed with licensing and location details. The dataset includes supplier names, unique IDs, full addresses, and license start and end dates. It is provided by the Colorado Department of State and was last updated in April 2026.
2026 research by Shuai Wang identifies candidate biomarkers and therapeutic targets for ankylosing spondylitis. The dataset contains results from transcriptomic profiling, Mendelian randomization analysis, and drug prediction, with findings validated by RT–qPCR on clinical blood samples. Specific genes RORA, FBXO31, and MSRB3 are highlighted as causally linked to disease risk.
Shuai Wang's 2026 figshare data sheet presents results from a transcriptomic and Mendelian randomization study on ankylosing spondylitis. The research identifies RORA, FBXO31, and MSRB3 as candidate biomarker genes with causal links to disease risk, validated by RT–qPCR. The dataset includes findings from functional enrichment, immune infiltration, and drug prediction analyses.
Research data identifies integrated stress response genes as biomarkers for ankylosing spondylitis. The study combines transcriptomic profiling of patient blood with Mendelian randomization analysis. Results highlight downregulation of RORA and FBXO31 and increased expression of MSRB3.
Shuai Wang's 2026 figshare study provides transcriptomic and Mendelian randomization data identifying integrated stress response genes as biomarkers for ankylosing spondylitis. The dataset includes results from differential expression analysis, causal inference, functional enrichment, immune infiltration, and drug prediction. Data is provided in a 37.6 KB XLSX file.
Transcriptomic and Mendelian randomization data identifies RORA, FBXO31, and MSRB3 as causal biomarkers for ankylosing spondylitis. The 35.8 KB Excel file contains results from differential gene expression analysis, causal inference, and drug prediction studies. Author Shuai Wang published the findings in 2026 under a CC BY 4.0 license.
A transcriptomic and Mendelian randomization study identifies candidate biomarkers and therapeutic targets for Ankylosing Spondylitis. The research includes differentially expressed genes like RORA, FBXO31, and MSRB3, validated via RT–qPCR in clinical blood samples. It provides analysis results on causal associations, functional enrichment, immune infiltration, and drug predictions.
39.6 KB Excel file contains transcriptomic and Mendelian randomization results identifying novel biomarkers for ankylosing spondylitis. Author Shuai Wang's study, updated March 2026, validated downregulation of RORA and FBXO31 and upregulation of MSRB3 in patient blood samples. The data supports causal inference and drug prediction analyses.
Transcriptomic and Mendelian randomization analysis identifies RORA, FBXO31, and MSRB3 as causal biomarkers for ankylosing spondylitis. The 147.0 KB dataset includes results from functional enrichment, immune infiltration analysis, and drug predictions for indirubin and pentoxifylline. Shuai Wang published the data on figshare under a CC-BY-4.0 license, with a last update in March 2026.
Research data identifies novel biomarkers for Ankylosing Spondylitis through transcriptomic profiling and Mendelian randomization analysis. The study demonstrates marked downregulation of RORA and FBXO31 and increased expression of MSRB3 in patient blood samples. Findings highlight causal contributions to disease risk and suggest potential therapeutic agents like indirubin and pentoxifylline.
17.5 KB of model comparison data in an XLS file, uploaded by Isabela S. Sirtoli to figshare. The dataset details the composition of multiple logistic regression models for a development cohort, comparing models with different variable sets. The final model includes statistically significant variables and an interaction term between airway surgery and tracheal intubation.
A clinical dataset from figshare stratifying patient characteristics by the occurrence of perioperative respiratory adverse events. The data, presented as counts and percentages, was authored by Isabela S. Sirtoli and last updated on April 21, 2026. The dataset is a 9.5 KB Excel file.
A list of medical items and services, excluding drugs, that require prior authorization. The data is provided by data.oregon.gov and was last updated on May 1, 2026. It includes procedure descriptions and associated codes for administrative reference.
Hospital admissions data for unintentional and deliberate injuries among young people aged 15-24, normalized per 10,000 population. The dataset originates from the Government Digital Service via the EU Open Data platform and is licensed under OGL-UK-3.0. The specific time range and geographic coverage are not detailed in the provided metadata.
Hospital admissions data for mental health conditions among individuals aged 0 to 17 years, standardized per 100,000 population. The dataset originates from the Government Digital Service and is published under the OGL-UK-3.0 license. The last update date and specific temporal or geographic coverage are not provided in the available metadata.