Revise README: unified intro, citation, public usage under openmed-community

README.md

@@ -10,8 +10,16 @@ size_categories:
   - 100K<n<1M
 ---
 
-# MultiCaRe Cases
+# MultiCaRe: Open-Source Clinical Case Dataset
 
+MultiCaRe is an open-source, multimodal clinical case dataset derived from PubMed Central’s Open Access (OA) Case Report articles. It links de-identified case narratives to figure images/captions and article-level metadata, enabling cross-modal supervision and retrieval.
+
+- Source and process: OA case reports from PMC; parsed metadata and abstracts; extracted case narratives; downloaded and processed figures; aligned captions; curated image taxonomy (>140 classes).
+- Scale: 85k+ articles with 110k+ patient mentions and 160k+ images (v2.0).
+- Tasks enabled: narrative classification, retrieval, summarization; multimodal modeling with image joins; VQA/doc-QA with figure references.
+- Citation: Paper — https://www.mdpi.com/2306-5729/10/8/123; Zenodo — https://zenodo.org/records/13936721.
+
+This repository: per-case dataset
 Per-case clinical narratives and demographics extracted from case reports.
 
 Schema
@@ -24,17 +32,15 @@ Schema
 Quick start
 ```python
 from datasets import load_dataset
-tok = "<token>"
-cases = load_dataset("MaziyarPanahi/multicare-cases", split="train", use_auth_token=tok)
+cases = load_dataset("openmed-community/multicare-cases", split="train")
 print(cases[0]["case_text"][:600])
 ```
 
 Join with images
 ```python
 from datasets import load_dataset
-tok = "<token>"
-cases = load_dataset("MaziyarPanahi/multicare-cases", split="train", use_auth_token=tok)
-imgs  = load_dataset("MaziyarPanahi/multicare-images", split="train", use_auth_token=tok)
+cases = load_dataset("openmed-community/multicare-cases", split="train")
+imgs  = load_dataset("openmed-community/multicare-images", split="train")
 
 cid = cases[0]["case_id"]
 imgs_for_case = imgs.filter(lambda e: e["patient_id"] == cid)