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Description
A large-scale collection of 366,518 X-ray medical images and associated reports with confirmed clinical findings, designed to support healthcare AI development. The dataset, created by InfoBayAI, captures authentic imaging characteristics such as scanner variability and acquisition protocols. It was last updated on June 2, 2026.
Use Cases
Train diagnostic AI models based on confirmed clinical findings.
Develop medical imaging classifiers using the large-scale collection of X-ray images.
Build natural language generation systems for radiology reports based on the detailed clinical narratives.
Study scanner variability and acquisition protocol effects on imaging data.
Strengths
Contains data from 194,524 patients, providing a substantial patient cohort.
Includes 366,518 medical images, offering a large-scale resource for training.
Designed to capture authentic imaging characteristics like scanner variability and patient positioning.
Limitations
Column-level documentation is absent; field semantics must be inferred after download.
Row count for the report data is unknown, which may limit suitability assessment.
Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
Source
InfoBayAI
Freshness
Last updated 2026-06-02 05:46:07; freshness should be verified.
License is unknown; terms of use must be verified before application.