upload hub_repos/ehr_rel/README.md to hub from bigbio repo

README.md

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+
+---
+language: 
+- en
+license: apache-2.0
+license_bigbio_shortname: APACHE_2p0
+pretty_name: EHR-Rel
+---
+
+
+# Dataset Card for EHR-Rel
+
+## Dataset Description
+
+- **Homepage:** https://github.com/babylonhealth/EHR-Rel
+- **Pubmed:** False
+- **Public:** True
+- **Tasks:** Semantic Similarity
+
+
+EHR-Rel is a novel open-source1 biomedical concept relatedness dataset consisting of 3630 concept pairs, six times more
+than the largest existing dataset.  Instead of manually selecting and pairing concepts as done in previous work,
+the dataset is sampled from EHRs to ensure concepts are relevant for the EHR concept retrieval task.
+A detailed analysis of the concepts in the dataset reveals a far larger coverage compared to existing datasets.
+
+
+
+## Citation Information
+
+```
+@inproceedings{schulz-etal-2020-biomedical,
+    title = {Biomedical Concept Relatedness {--} A large {EHR}-based benchmark},
+    author = {Schulz, Claudia  and
+      Levy-Kramer, Josh  and
+      Van Assel, Camille  and
+      Kepes, Miklos  and
+      Hammerla, Nils},
+    booktitle = {Proceedings of the 28th International Conference on Computational Linguistics},
+    month = {dec},
+    year = {2020},
+    address = {Barcelona, Spain (Online)},
+    publisher = {International Committee on Computational Linguistics},
+    url = {https://aclanthology.org/2020.coling-main.577},
+    doi = {10.18653/v1/2020.coling-main.577},
+    pages = {6565--6575},
+    }
+
+```