Update README.md

README.md

@@ -32,4 +32,73 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-nc-sa-4.0
+language:
+- en
+tags:
+- patient summary
+- medical
+- biology
+size_categories:
+- 100K<n<1M
 ---
+*This is a dataset repository made for the AISC class at Harvard Medical School. Please find the original dataset repository here:https://huggingface.co/datasets/zhengyun21/PMC-Patients*
+
+# Dataset Card for PMC-Patients
+
+## Dataset Description
+
+- **Homepage:** https://github.com/pmc-patients/pmc-patients
+- **Repository:** https://github.com/pmc-patients/pmc-patients
+- **Paper:** https://arxiv.org/pdf/2202.13876.pdf
+- **Leaderboard:** https://pmc-patients.github.io/
+- **Point of Contact:** zhengyun21@mails.tsinghua.edu.cn
+
+### Dataset Summary
+
+**PMC-Patients** is a first-of-its-kind dataset consisting of 167k patient summaries extracted from case reports in PubMed Central (PMC), 3.1M patient-article relevance and 293k patient-patient similarity annotations defined by PubMed citation graph.
+
+
+### Supported Tasks and Leaderboards
+
+**This is purely the patient summary dataset with relational annotations. For ReCDS benchmark, refer to [this dataset](https://huggingface.co/datasets/zhengyun21/PMC-Patients-ReCDS)**
+
+Based on PMC-Patients, we define two tasks to benchmark Retrieval-based Clinical Decision Support (ReCDS) systems: Patient-to-Article Retrieval (PAR) and Patient-to-Patient Retrieval (PPR). 
+For details, please refer to [our paper](https://arxiv.org/pdf/2202.13876.pdf) and [leaderboard](https://pmc-patients.github.io/).
+
+### Languages
+
+English (en).
+
+## Dataset Structure
+
+### PMC-Paitents.csv
+
+This file contains all information about patients summaries in PMC-Patients, with the following columns:
+
+- `patient_id`: string. A continuous id of patients, starting from 0.
+- `patient_uid`: string. Unique ID for each patient, with format PMID-x, where PMID is the PubMed Identifier of the source article of the patient and x denotes index of the patient in source article.
+- `PMID`: string. PMID for source article.
+- `file_path`: string. File path of xml file of source article.
+- `title`: string. Source article title.
+- `patient`: string. Patient summary.
+- `age`: list of tuples. Each entry is in format `(value, unit)` where value is a float number and unit is in 'year', 'month', 'week', 'day' and 'hour' indicating age unit. For example, `[[1.0, 'year'], [2.0, 'month']]` indicating the patient is a one-year- and two-month-old infant.
+- `gender`: 'M' or 'F'. Male or Female.
+- `relevant_articles`: dict. The key is PMID of the relevant articles and the corresponding value is its relevance score (2 or 1 as defined in the ``Methods'' section).
+- `similar_patients`: dict. The key is patient_uid of the similar patients and the corresponding value is its similarity score (2 or 1 as defined in the ``Methods'' section).
+## Dataset Creation
+If you are interested in the collection of PMC-Patients and reproducing our baselines, please refer to [this reporsitory](https://github.com/zhao-zy15/PMC-Patients).
+### Citation Information
+If you find PMC-Patients helpful in your research, please cite our work by:
+```
+@article{zhao2023large,
+  title={A large-scale dataset of patient summaries for retrieval-based clinical decision support systems},
+  author={Zhao, Zhengyun and Jin, Qiao and Chen, Fangyuan and Peng, Tuorui and Yu, Sheng},
+  journal={Scientific Data},
+  volume={10},
+  number={1},
+  pages={909},
+  year={2023},
+  publisher={Nature Publishing Group UK London}
+}
+```