Dataset research report
Chest Xray Classification research report
A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.
Executive Summary
Dataset Labels ['NORMAL', 'PNEUMONIA'] Number of Images {'train': 4077, 'test': 582, 'valid': 1165} How to Use Install datasets: pip install datasets Load the dataset: from datasets import load_dataset ds = load_dataset("keremberke/chest-xray-classification", name="full") example = ds['train'][0] Roboflow Dataset Page https://universe.roboflow.com/mohamed-traore-2ekkp/chest-x-rays-qjmia/dataset/2 Citation… See the full description on the dataset page: https://huggingface.co/datasets/keremberke/chest-xray-classification.
Follow-Up Queries
Method And Limits
- Load the catalog entry and preview rows from the processed dataset file.
- Infer numeric, categorical, time, and location fields from real columns.
- Generate a small set of defensive Plotly chart specifications from that profile.
- Expose each chart idea as a query link so the report can be rerun or exported in Helix.
This report is intentionally reproducible. It uses the local catalog metadata and generated chart specifications rather than claiming external conclusions beyond the dataset.