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--- |
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license: apache-2.0 |
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tags: |
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- biomedical |
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- text-retrieval |
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- abstract-retrieval |
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--- |
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# PubMed Dataset Loader (Configurable 2014-2025) - Full Abstract Parsing |
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## Overview |
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This repository provides a modified Hugging Face `datasets` loading script for MEDLINE/PubMed data. It is designed to download and parse PubMed baseline XML files, with specific enhancements for **extracting the complete text from structured abstracts**. |
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This script is based on the original NCBI PubMed dataset loader from Hugging Face and includes modifications by **[Hoang Ha (LIG)](https://www.linkedin.com/in/hoanghavn/)** and abstract parsing enhancements was adapted for the **[NanoBubble Project](https://nanobubbles.hypotheses.org/)** contributed by **Tiziri Terkmani (Research Engineer, LIG, Team SIGMA)**. |
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## Key Features |
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- Parses PubMed baseline XML files (`.xml.gz`). |
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- **Full Abstract Extraction:** Correctly handles structured abstracts (e.g., BACKGROUND, METHODS, RESULTS) and extracts the complete text, unlike some previous parsers that might truncate. |
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- **Configurable Date Range:** Intended for use with data from **2015 to 2025**, but **requires manual configuration** of the download URLs within the script (`pubmed_fulltext_dataset.py`). |
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- Generates data compatible with the Hugging Face `datasets` library schema. |
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## Dataset Information |
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- **Intended Time Period:** 2015 - 2025 (Requires user configuration) |
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- **Data Source:** U.S. National Library of Medicine (NLM) FTP server. |
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- **License:** Apache 2.0 (for the script), NLM terms apply to the data itself. |
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- **Size:** Variable depending on configured download range. The full 2015-2025 range contains 14 millions of abstracts. |
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## !! Important Caution !! |
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The Python script (`pubmed_fulltext_dataset.py`) **requires manual modification** to download the desired data range (e.g., 2015-2025). The default configuration only downloads a *small sample* of files from the 2025 baseline for demonstration purposes. |
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**You MUST edit the `_URLs` list in the script** to include the paths to **ALL** the `.xml.gz` files for **each year** you want to include. |
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**How to Configure URLs:** |
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1. Go to the NLM FTP baseline directory: [ftp://ftp.ncbi.nlm.nih.gov/pubmed/baseline/](ftp://ftp.ncbi.nlm.nih.gov/pubmed/baseline/) |
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2. For each year (e.g., 2015, 2016, ..., 2025), identify all the `pubmedYYnXXXX.xml.gz` files. The number of files (`XXXX`) varies per year. Checksum files (e.g., `pubmed24n.xml.gz.md5`) often list all files for that year. |
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3. Construct the full URL for each file (e.g., `https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmedYYnXXXX.xml.gz`). |
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4. Add all these URLs to the `_URLs` list in the script. See the comments within the script for examples. |
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**Use this loader with caution and always verify the scope of the data you have actually downloaded and processed.** |
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## Usage |
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To use this script to load the data (after configuring the `_URLs` list): |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("HoangHa/pubmed25_debug", split="train", trust_remote_code=True, cache_dir=".") |
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print(dataset) |
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print(dataset['train'][0]['MedlineCitation']['Article']['Abstract']['AbstractText']) |
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``` |
