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---
dataset_info:
features:
- name: patient_id
dtype: int64
- name: patient_uid
dtype: string
- name: PMID
dtype: int64
- name: file_path
dtype: string
- name: title
dtype: string
- name: patient
dtype: string
- name: age
dtype: string
- name: gender
dtype: string
- name: relevant_articles
dtype: string
- name: similar_patients
dtype: string
splits:
- name: train
num_bytes: 547684991
num_examples: 167034
download_size: 298274057
dataset_size: 547684991
configs:
- config_name: default
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:** [email protected]
### 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}
}
``` |