README.md

metadata

license: cc-by-4.0
task_categories:
  - text-classification
language:
  - en
tags:
  - medical
  - systematic-review
  - research-papers
pretty_name: Combined Medical Systematic Reviews
size_categories:
  - 1K<n<10K

🏥 Combined Medical Systematic Reviews Dataset

Dataset Description

This dataset combines 23 systematic review datasets from various medical domains, totaling 135 papers. The dataset includes papers from systematic reviews in fields such as virology, dementia, anxiety disorders, and general medical research.

Data Fields

The dataset includes the following standardized fields:

• title: The title of the paper
• abstract: The paper's abstract
• year: Publication year (when available, -1 if not available)
• dataset_name: The source dataset name
• dataset_domain: The medical domain of the source dataset

Source Datasets

The following datasets were combined (sorted by number of papers):

Dataset	Papers	Domain
kwok_2020	6	medical
wolters_2018	6	medical
bos_2018	6	medical
bannach-brown_2019	6	medical
van_dis_2020	6	medical
donners_2021	6	medical
muthu_2021	6	medical
leenaars_2020	6	medical
jeyaraman_2020	6	medical
meijboom_2021	6	medical
menon_2022	6	medical
smid_2020	6	medical
welling_2021	6	medical
appenzeller-herzog_2019	6	medical
moran_2021	6	medical
van_der_waal_2022	6	medical
oud_2018	6	medical
leenaars_2019	6	medical
van_de_schoot_2018	6	medical
van_der_valk_2021	6	medical
sep_2021	6	medical
muthu_2022	5	medical
brouwer_2019	4	medical

Usage

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("sumuks/combined_medical_reviews")

# Access the papers
papers = dataset["train"]

# Example: Get papers from a specific domain
dementia_papers = papers.filter(lambda x: "dementia" in x["dataset_domain"].lower())

# Example: Get papers from a specific year
papers_2020 = papers.filter(lambda x: x["year"] == 2020)

Dataset Creation

This dataset was created by:

1. Collecting systematic review datasets from the ASReview SYNERGY dataset
2. Fetching paper metadata (title, abstract, year) from OpenAlex API
3. Standardizing and combining the data into a single dataset
4. Removing duplicates based on title and abstract

Limitations

• The dataset contains only a sample of papers from each source dataset
• Some papers may be missing abstracts or other metadata
• The dataset focuses on English-language papers
• The quality of metadata depends on OpenAlex data

Citation

When using this dataset, please cite both this dataset and the original ASReview SYNERGY dataset:

@misc{combined_medical_reviews,
    title = {Combined Medical Systematic Reviews Dataset},
    author = {OpenHands AI},
    year = {2024},
    publisher = {Hugging Face},
    url = {https://huggingface.co/datasets/sumuks/combined_medical_reviews}
}

License

This dataset is released under CC-BY 4.0 license. The data inherits licenses from:

1. ASReview SYNERGY dataset
2. OpenAlex API data