metadata

license: mit
task_categories:
  - text-generation
language:
  - en
tags:
  - pubmed embedding
size_categories:
  - 100M<n<1B

PubMed Embeddings Dataset

This dataset contains embeddings generated from the PubMed dataset, which can be found at https://huggingface.co/datasets/ncbi/pubmed. The embeddings were created using the NeuML/pubmedbert-base-embedding model.

Dataset Structure

Each line in the dataset represents a single embedding in the form of a list. The format for each entry is defined as follows:

node.id_ = f"node-{tpubmed}-{idx}"
node.metadata["title"] = ttitle
node.metadata["author"] = firstAuthor
node.metadata["pubmed"] = tpubmed
node.metadata["date"] = tdate
node.metadata["key"] = tpubmed
node.metadata["source"] = "Pubmed"

node.id_: A unique identifier for each node, formatted as node-{tpubmed}-{idx}, where tpubmed is the PubMed ID and idx is the index of the entry.
node.metadata["title"]: The title of the PubMed article.
node.metadata["author"]: The first author of the PubMed article.
node.metadata["pubmed"]: The PubMed ID of the article.
node.metadata["date"]: The publication date of the article.
node.metadata["key"]: The PubMed ID of the article (same as node.metadata["pubmed"]).
node.metadata["source"]: The source of the data, which is always "Pubmed".

Usage

To use this dataset, you can load it into your preferred data processing library or tool. Each line in the dataset represents a single embedding, and the metadata associated with each embedding can be accessed using the keys defined in the format above.

Original Data Source

The original data used to create these embeddings can be found at https://huggingface.co/datasets/ncbi/pubmed. Please refer to the documentation and license of the original dataset for more information on its contents and usage.

Embedding Model

The embeddings in this dataset were generated using the NeuML/pubmedbert-base-embedding model. For more information on the model and its performance, please refer to the model's documentation.

This dataset card aims to be a base template for new datasets. It has been generated using this raw template.

Uses

Direct Use

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Dataset Structure

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Dataset Creation

Curation Rationale

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Source Data

Data Collection and Processing

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Personal and Sensitive Information

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Bias, Risks, and Limitations

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Recommendations

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