Data · dataset · 2025
Primary Breast Cancer Clinical Dataset from Epic Hospital (Breast_Cancer_METABRIC_Epic_Hospital)
Listed in Teesside University Research Data Repository
This dataset contains clinical features of breast tumors, designed for use in machine learning and AI-based classification tasks.
Description
Each row represents a patient sample with numeric attributes describing tumor characteristics. The dataset includes labels for diagnosis (benign vs malignant), making it suitable for supervised learning tasks such as classification, feature selection, and explainable AI studies.
This dataset contains 15,054 breast cancer patient records collected from Epic Hospital. It provides a comprehensive set of clinical, demographic, and pathological features relevant to breast cancer prognosis and treatment analysis. The dataset includes 34 columns, such as patient demographics (age, sex), clinical details (tumor size, tumor stage, grade, histologic subtype), treatment history (surgery, chemotherapy, hormone therapy, radiotherapy), and survival outcomes (overall survival months, overall survival status, relapse status).
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The dataset is intended to support machine learning, statistical modeling, and medical research in breast cancer survival prediction, treatment response analysis, and outcome assessment. The dataset may be applied to: => Predictive modeling for early breast cancer detection => Feature importance and interpretability studies => Benchmarking traditional ML models vs. LLM-based tabular learning approaches. Researchers and practitioners may use this dataset for academic, educational, or applied AI purposes.
Links
Where it is published
- DOI doi.org/10.17632/dbz42w9x8h.4 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/dbz42w9x8h.4 | 15 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[disease].local:disease:cancer | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].anzsrc:field:320701 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Medical Bacteriology'] |
| concepts[field].anzsrc:group:4611 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Machine Learning'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:tabular | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |