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Medical imaging (X-ray, CT, MRI), electronic health records, clinical trials, ECG/EEG, pathology
13,592 datasets
Retinal images categorized into Optic Nerve Head (ONH) and macular glaucoma segmentation classes. These data points enable the training of models for anatomical boundary detection and glaucoma diagnosis through image-based clinical assessment.
5,856 pediatric chest X-ray images categorized into 'Normal' and 'Pneumonia' classes. The collection includes 1,583 normal cases and 4,273 pneumonia cases, with the latter further subdivided into bacterial and viral etiologies.
1,338 individual medical insurance records across four geographic regions. The data tracks seven demographic and health features including age, body mass index, and smoking status alongside the resulting medical charges.
130 CT scans specifically curated for liver and tumor segmentation tasks. The dataset consists of volumetric medical imaging data designed to facilitate the identification of pathological growths within liver anatomy.
Patient health records categorized by clinical features for the prediction of diabetes status. The dataset facilitates binary classification tasks to determine the likelihood of a diabetes diagnosis based on health-related predictors.
27,558 segmented cell images categorized into parasitized and uninfected classes for malaria detection. The collection includes images derived from Giemsa-stained thin blood smear slides of 150 infected and 50 healthy patients.
888 low-dose CT scans containing 1,186 annotated lung nodules verified by multiple radiologists. The data includes spatial coordinates for nodule candidates and diameter measurements for confirmed lesions across 10 subsets.
State-reported data details Medicaid-covered outpatient drug utilization and payments. It includes state, drug name, National Drug Code, prescription counts, and reimbursement dollars. The data is reported by state Medicaid agencies and was last updated in December 2025.
U.S. Department of Health & Human Services provides State Drug Utilization Data for 2024, detailing Medicaid-covered outpatient drug purchases. The dataset includes state, drug name, National Drug Code, number of prescriptions, and dollars reimbursed. It is sourced from state reports to the Medicaid Drug Rebate Program.
The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge-level detail on patient characteristics, diagnoses, treatments, services, and charges for 2023. This de-identified data is published by health.data.ny.gov and does not contain protected health information (PHI). The dataset was last updated on October 10, 2025.
The DENTEX dataset was released for the Dental Enumeration and Diagnosis on Panoramic X-rays Challenge organized with MICCAI in 2023. Its primary objective is to develop algorithms for accurately detecting abnormal teeth with enumeration and diagnosis. The dataset is authored by ibrahimhamamci and was last updated on December 5, 2025.
A dataset of chest X-ray images processed for binary classification tasks (Normal vs. Anomaly). It was created by inGeniia for a Deep Learning course, teaching Convolutional Neural Networks and Transfer Learning with models like YOLO11 in classification mode. The dataset was last updated on December 8, 2025.
New York's SPARCS de-identified file provides discharge-level detail on patient characteristics, diagnoses, treatments, and charges. The data is maintained by health.data.ny.gov and was last updated in October 2025. Columns suggest information on total costs, length of stay, severity of illness, and patient disposition.
Cleaned Form 5500 data from the Department of Labor, used to produce annual Bulletins on private pension plans, group health plans, and Direct Filing Entities. The dataset includes 'spread' files for mapping DFE holdings to underlying assets. It was last updated in January 2026.
Medicare Part D data details spending for drugs prescribed to beneficiaries who self-administer medication. It focuses on average spending per dosage unit and changes over time, including manufacturer spending and drug use information. The dataset is provided by the U.S. Department of Health & Human Services and was last updated in December 2025.
Medicare Part B spending data details payments for drugs administered in outpatient settings to enrollees. The dataset focuses on average spending per dosage unit and its change over time, and includes consumer-friendly descriptions of drug uses and manufacturers. It is published by the U.S. Department of Health & Human Services and was last updated in December 2025.
U.S. Medicaid data presents information on spending for covered outpatient drugs prescribed to beneficiaries. The dataset focuses on average spending per dosage unit and its change over time, including manufacturer spending and consumer-friendly drug use information. It is published by the U.S. Department of Health & Human Services and was last updated in December 2025.
Medicare Geographic Variation data provides demographic, spending, use, and quality indicators for the Original Medicare population. The dataset covers national, state, and county levels, including the District of Columbia, Puerto Rico, and the Virgin Islands. Spending figures are standardized to remove geographic differences in payment rates.
800 episodes of robot manipulation data collected from a proficient human operator performing four distinct tasks: lifting a cube, picking and placing a can, squaring, and tool hanging. The dataset was created using LeRobot and is formatted for training Vision-Language-Action (VLA) models like OpenPI. It was uploaded to Hugging Face by yananchen and last updated on December 5, 2025.
Asthma hospitalization counts and rates per 10,000 residents for California statewide and by county. Data are stratified by age groups (all ages, 0-17, 18+, 0-4, 5-17, 18-64, 65+) and race/ethnicity categories (white, black, Hispanic, Asian/Pacific Islander, American Indian/Alaskan Native). The dataset is derived from patient discharge data from all licensed hospitals in California.