File size: 2,039 Bytes
1e64385 55f1f70 1e64385 55f1f70 efa423f 86b4813 55f1f70 439517f 55f1f70 439517f 55f1f70 439517f 55f1f70 754dc11 55f1f70 86b4813 55f1f70 86b4813 55f1f70 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 |
---
license: cc-by-nc-sa-4.0
language:
- en
tags:
- biology
- medical
size_categories:
- 100K<n<1M
---
# Dataset Card
<!-- Provide a quick summary of the dataset. -->
This dataset consists of abstracts from heart-related papers collected from PubMed. It can be used for pre-training a language model specialized in cardiology.
The dataset was collected through the PubMed API, based on the names of heart-related journals and a glossary of cardiology terms.
# Dataset
## Data Sources
- **[Pubmed](https://pubmed.ncbi.nlm.nih.gov/)**: PubMed is a database that provides abstracts of research papers related to life sciences, biomedical fields, health psychology, and health and welfare. Among these, we have collected abstracts of papers related to the heart.
## Keywords Sources
- **[Scimago Journal & Country Rank](https://www.scimagojr.com/journalrank.php?category=2705#google_vignette)** : We used a list of cardiology-related journals provided by SJR as keywords for data collection.
- **[National Institutes of Health](https://www.nia.nih.gov/health/heart-health/heart-health-glossary)** : We used a glossary provided by NIH as keywords for data collection.
- **[The Texas Heart Institute](https://www.texasheart.org/heart-health/heart-information-center/topics/a-z)** : We used a glossary provided by Texas Heart Institute as keywords for data collection.
- **[Aiken Physicians Alliance](https://aikenphysicians.com/services/cardiology/cardiology-glossary-of-terms)** : We used a glossary provided by Aiken Physicians Alliance as keywords for data collection.
## Dataset Field
| Field | Data Type | Description |
| --- | --- | --- |
| title | string | The title of the paper. |
| abst | string | The abstract of the paper. |
## Dataset Structure
```python
DatasetDict({
train: Dataset({
features: ['title', 'abst'],
num_rows: 2600900
})
})
```
## Use
```python
from datasets import load_dataset
dataset = load_dataset("InMedData/Cardio_v1")
```
### Dataset Contact
[email protected]
|