Can I use this for systematic reviews?

Yes, the skill includes specific strategies for the PICO framework and advanced filters to find systematic reviews, meta-analyses, and clinical trials.

How do I filter by specific publication dates?

You can use the [dp] field tag, such as '2023:2024[dp]' for a range or '2024[dp]' for a specific year, within your search queries.

Does this skill require an NCBI API key?

While not strictly required for low-volume searches, using an NCBI API key is recommended as it increases rate limits from 3 to 10 requests per second.

Should I use Biopython with this skill?

For Python-based workflows, the skill explicitly recommends using biopython (Bio.Entrez), though it provides direct REST API guidance for other environments.

PubMed Database & API Toolkit

Name: PubMed Database & API Toolkit
Author: sickn33

bysickn33

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31,721

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Ciencia de Datos y ML

Interfaces with the U.S. National Library of Medicine's PubMed database using advanced Boolean queries and E-utilities REST APIs.

This skill empowers Claude to perform sophisticated biomedical and life sciences literature research directly within the PubMed database. It provides comprehensive support for constructing complex queries using MeSH terms, Boolean operators, and field tags, while also facilitating programmatic data retrieval through the NCBI E-utilities API. Whether you are conducting systematic reviews, managing citations, or building automated workflows for data extraction, this skill offers the necessary logic and documentation to navigate MEDLINE records and retrieve metadata or full-text articles efficiently.

Características Principales

01Systematic literature review filtering using the PICO framework

02Programmatic access via NCBI E-utilities (ESearch, EFetch, ESummary, etc.)

03Batch processing capabilities for bulk data extraction and monitoring

04Automated citation matching and identifier retrieval for PMIDs and DOIs

0531,721 GitHub stars

06Advanced Boolean and MeSH query construction for precise medical searches

Casos de Uso

01Building automated workflows to monitor specific journals or authors for new publications

02Automating the extraction of biomedical abstracts for data science and NLP tasks

03Conducting systematic meta-analyses and literature reviews for clinical research

Características Principales

01Systematic literature review filtering using the PICO framework

02Programmatic access via NCBI E-utilities (ESearch, EFetch, ESummary, etc.)

03Batch processing capabilities for bulk data extraction and monitoring

04Automated citation matching and identifier retrieval for PMIDs and DOIs

0531,721 GitHub stars

06Advanced Boolean and MeSH query construction for precise medical searches

Casos de Uso

01Building automated workflows to monitor specific journals or authors for new publications

02Automating the extraction of biomedical abstracts for data science and NLP tasks

03Conducting systematic meta-analyses and literature reviews for clinical research