metadata

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

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 and leaderboard.

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.

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}
}