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Medical imaging (X-ray, CT, MRI), electronic health records, clinical trials, ECG/EEG, pathology
13,201 datasets
Brazilian National Health Survey data from 2013 provides prevalence estimates for arterial hypertension in adults based on three diagnostic criteria: self-reported, measured by instrument, and measured or medication use. The dataset includes 60,202 individuals and presents prevalence rates with 95% confidence intervals, broken down by gender, age, urban/rural status, and geographic region. The study was authored by Déborah Carvalho Malta.
An electrocardiogram (ECG) dataset published on Kaggle. The title suggests it contains ECG signals, potentially focusing on RR interval length. Metadata is minimal; the specific number of records, collection period, and originating institution are unknown.
A collection of X-ray medical images published on Kaggle. The dataset's specific size, source, and collection period are not detailed in the available metadata. Its content and structure require verification after download.
Greater London Authority modelling estimates the long-term health impacts of air pollution exposure in London from 2016 to 2050. The study projects that policies in the London Environment Strategy will result in nearly 300,000 fewer new pollution-related diseases and around one million fewer hospital admissions by 2050. Results are provided per 100,000 residents by London borough.
Complaint records received by the New York State Ombudsman Program, which advocates for residents of nursing homes, assisted living, and other licensed adult care facilities. The dataset likely contains details of issues reported, mediation efforts, and referrals to state agencies. It is published by the State of New York and includes records from 2020 onward.
SenTSR-Bench is a de-identified, real-world multivariate time-series benchmark for diagnostic reasoning. It was released by Zelin He and collaborators as part of a research paper titled 'SenTSR-Bench: Thinking with Injected Knowledge for Time-Series Reasoning'.
100 de-identified clinical reports from Internal Medicine and Emergency Departments containing physician-inserted medical errors, created by Vrda for the Clinipal project in 2026. This dataset provides a specialized ground truth for evaluating AI systems designed to detect patient safety risks in clinical documentation.
Featuring results from a randomized strategy trial comparing maternal antiretroviral therapy (mART) versus infant nevirapine prophylaxis (iNVP) for preventing mother-to-child HIV transmission during breastfeeding. The trial enrolled 2431 mother-infant pairs across 14 sites in Sub-Saharan Africa and India between June 2011 and October 2014. The primary outcome was confirmed infant HIV-1 infection, with high infant HIV-free survival rates of 97.1% (mART) and 97.7% (iNVP) at 24 months.
Aggregating 1,035 evaluable participants from the A5322 (HAILO) long-term observational study. Participants were aged 40 or older, ART-naïve at entry into the parent ALLRT study, and were followed for approximately 7 years (336 weeks) to evaluate clinical, virologic, and immunologic outcomes associated with aging and long-term ART.
Retinal_test_images is a dataset of medical images from the eye's retina, published on Kaggle. The dataset's specific content, scale, and origin are not detailed in the provided metadata. Further verification after download is required to confirm the number of images, their annotations, and the collection methodology.
A dataset titled 'IDM_30_LENGTH_RR_ECG_BANAUNU_KO_LAGI' published on Kaggle. The title suggests it likely contains electrocardiogram (ECG) signal data, possibly focusing on RR interval lengths. The author, organization, and specific temporal coverage are unknown.
Batch1_ECG is a dataset of electrocardiogram signals. It is hosted on Kaggle, but its author, organization, and creation date are unknown. The dataset's size, number of records, and specific column structure are not documented.
Batch2_ECG is a dataset of electrocardiogram signals published on Kaggle. The specific number of records, time range, and collection methodology are not detailed in the available metadata. Its content likely contains time-series voltage measurements from ECG leads.
batch3_ecg is a dataset of electrocardiogram (ECG) signals published on Kaggle. The dataset's specific size, collection method, and origin are not detailed in the provided metadata. Its content likely contains time-series data representing heart electrical activity.
Batch4 ECG is a dataset of electrocardiogram signals, likely containing time-series voltage readings. It is hosted on Kaggle, but its specific size, origin, and collection date are unknown. The dataset's content and structure must be verified after download.
Batch6 ECG is an electrocardiogram dataset published on Kaggle. The dataset's author, organization, and specific collection details are unknown. Its size, row count, and temporal coverage are also unspecified.
Batch7 ECG is a dataset of electrocardiogram signals published on Kaggle. The dataset's author, organization, and specific collection details are not provided in the available metadata. Its size, temporal coverage, and exact contents require verification after download.
Kaggle hosts this dataset of electrocardiogram (ECG) signals. The title suggests it is the fifth batch of a larger ECG data collection. The dataset's author, organization, and specific scale are unknown.
Batch8 ECG is a collection of electrocardiogram signals, likely containing time-series voltage recordings from the heart. The dataset is hosted on Kaggle, but its specific source, size, and collection details are not provided in the metadata. Its content and potential for medical or machine learning analysis require verification after download.
A collection of electrocardiogram (ECG) signals, likely representing heart activity over time. The dataset is hosted on Kaggle, but its specific source, size, and collection period are not detailed in the provided metadata. Further details about the data's origin, scale, and recording conditions require verification after download.