| --- |
| pretty_name: MultiCaRe Articles |
| license: cc-by-4.0 |
| task_categories: |
| - text-classification |
| - text-retrieval |
| language: |
| - en |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # MultiCaRe: Open-Source Clinical Case Dataset |
|
|
| MultiCaRe aggregates open-access, de-identified clinical case reports from PubMed Central’s OA corpus, pairing article-level metadata and abstracts with case narratives and figure images/captions. The normalization makes it easy to map from images → cases → articles. |
|
|
| - Source and process: parse PMC OA case reports; extract metadata/abstracts; download/process figures; align captions; build a hierarchical taxonomy for image labels. |
| - Scale: 85k+ OA articles, 160k+ images (v2.0). |
| - Tasks: article-level retrieval/classification, summarization; joins to cases/images for multimodal tasks. |
| - Citation: MDPI DATA paper — <https://www.mdpi.com/2306-5729/10/8/123>; Zenodo — <https://zenodo.org/records/13936721>. |
|
|
| This repository: per-article dataset |
| Per-article dataset with bibliographic metadata and abstracts (one file: articles.parquet). |
|
|
| Schema |
|
|
| - article_id: PMCID (primary key) |
| - title, journal, year |
| - doi, pmid, pmcid |
| - mesh_terms, major_mesh_terms, keywords |
| - link, license, case_amount |
| - abstract: article abstract |
| |
| Quick start |
| |
| ```python |
| from datasets import load_dataset |
| art = load_dataset("openmed-community/multicare-articles", split="train") |
| row = art[0] |
| print(row["title"]) |
| print(row["abstract"][:600]) |
| ``` |
| |
| Join examples |
| |
| ```python |
| from datasets import load_dataset |
| art = load_dataset("openmed-community/multicare-articles", split="train") |
| cas = load_dataset("openmed-community/multicare-cases", split="train") |
|
|
| aid = cas[0]["article_id"] |
| article = art.filter(lambda e: e["article_id"] == aid)[0] |
| print(article["title"]) # matching article |
| ``` |
| |
| Notes |
| |
| - Use article-level splits to avoid leakage when combining with images/cases. |
| |
