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skills/citation-management/references/pubmed_search.md
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skills/citation-management/references/pubmed_search.md
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# PubMed Search Guide
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Comprehensive guide to searching PubMed for biomedical and life sciences literature, including MeSH terms, field tags, advanced search strategies, and E-utilities API usage.
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## Overview
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PubMed is the premier database for biomedical literature:
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- **Coverage**: 35+ million citations
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- **Scope**: Biomedical and life sciences
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- **Sources**: MEDLINE, life science journals, online books
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- **Authority**: Maintained by National Library of Medicine (NLM) / NCBI
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- **Access**: Free, no account required
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- **Updates**: Daily with new citations
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- **Curation**: High-quality metadata, MeSH indexing
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## Basic Search
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### Simple Keyword Search
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PubMed automatically maps terms to MeSH and searches multiple fields:
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```
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diabetes
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CRISPR gene editing
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Alzheimer's disease treatment
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cancer immunotherapy
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```
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**Automatic Features**:
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- Automatic MeSH mapping
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- Plural/singular variants
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- Abbreviation expansion
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- Spell checking
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### Exact Phrase Search
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Use quotation marks for exact phrases:
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```
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"CRISPR-Cas9"
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"systematic review"
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"randomized controlled trial"
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"machine learning"
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```
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## MeSH (Medical Subject Headings)
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### What is MeSH?
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MeSH is a controlled vocabulary thesaurus for indexing biomedical literature:
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- **Hierarchical structure**: Organized in tree structures
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- **Consistent indexing**: Same concept always tagged the same way
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- **Comprehensive**: Covers diseases, drugs, anatomy, techniques, etc.
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- **Professional curation**: NLM indexers assign MeSH terms
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### Finding MeSH Terms
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**MeSH Browser**: https://meshb.nlm.nih.gov/search
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**Example**:
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```
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Search: "heart attack"
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MeSH term: "Myocardial Infarction"
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```
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**In PubMed**:
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1. Search with keyword
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2. Check "MeSH Terms" in left sidebar
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3. Select relevant MeSH terms
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4. Add to search
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### Using MeSH in Searches
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**Basic MeSH search**:
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```
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"Diabetes Mellitus"[MeSH]
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"CRISPR-Cas Systems"[MeSH]
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"Alzheimer Disease"[MeSH]
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"Neoplasms"[MeSH]
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```
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**MeSH with subheadings**:
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```
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"Diabetes Mellitus/drug therapy"[MeSH]
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"Neoplasms/genetics"[MeSH]
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"Heart Failure/prevention and control"[MeSH]
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```
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**Common subheadings**:
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- `/drug therapy`: Drug treatment
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- `/diagnosis`: Diagnostic aspects
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- `/genetics`: Genetic aspects
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- `/epidemiology`: Occurrence and distribution
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- `/prevention and control`: Prevention methods
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- `/etiology`: Causes
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- `/surgery`: Surgical treatment
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- `/metabolism`: Metabolic aspects
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### MeSH Explosion
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By default, MeSH searches include narrower terms (explosion):
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```
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"Neoplasms"[MeSH]
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# Includes: Breast Neoplasms, Lung Neoplasms, etc.
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```
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**Disable explosion** (exact term only):
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```
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"Neoplasms"[MeSH:NoExp]
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```
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### MeSH Major Topic
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Search only where MeSH term is a major focus:
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```
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"Diabetes Mellitus"[MeSH Major Topic]
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# Only papers where diabetes is main topic
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```
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## Field Tags
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Field tags specify which part of the record to search.
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### Common Field Tags
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**Title and Abstract**:
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```
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cancer[Title] # In title only
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treatment[Title/Abstract] # In title or abstract
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"machine learning"[Title/Abstract]
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```
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**Author**:
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```
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"Smith J"[Author]
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"Doudna JA"[Author]
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"Collins FS"[Author]
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```
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**Author - Full Name**:
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```
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"Smith, John"[Full Author Name]
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```
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**Journal**:
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```
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"Nature"[Journal]
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"Science"[Journal]
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"New England Journal of Medicine"[Journal]
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"Nat Commun"[Journal] # Abbreviated form
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```
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**Publication Date**:
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```
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2023[Publication Date]
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2020:2024[Publication Date] # Date range
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2023/01/01:2023/12/31[Publication Date]
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```
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**Date Created**:
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```
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2023[Date - Create] # When added to PubMed
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```
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**Publication Type**:
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```
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"Review"[Publication Type]
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"Clinical Trial"[Publication Type]
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"Meta-Analysis"[Publication Type]
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"Randomized Controlled Trial"[Publication Type]
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```
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**Language**:
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```
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English[Language]
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French[Language]
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```
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**DOI**:
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```
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10.1038/nature12345[DOI]
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```
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**PMID (PubMed ID)**:
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```
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12345678[PMID]
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```
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**Article ID**:
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```
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PMC1234567[PMC] # PubMed Central ID
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```
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### Less Common But Useful Tags
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```
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humans[MeSH Terms] # Only human studies
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animals[MeSH Terms] # Only animal studies
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"United States"[Place of Publication]
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nih[Grant Number] # NIH-funded research
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"Female"[Sex] # Female subjects
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"Aged, 80 and over"[Age] # Elderly subjects
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```
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## Boolean Operators
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Combine search terms with Boolean logic.
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### AND
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Both terms must be present (default behavior):
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```
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diabetes AND treatment
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"CRISPR-Cas9" AND "gene editing"
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cancer AND immunotherapy AND "clinical trial"[Publication Type]
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```
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### OR
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Either term must be present:
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```
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"heart attack" OR "myocardial infarction"
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diabetes OR "diabetes mellitus"
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CRISPR OR Cas9 OR "gene editing"
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```
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**Use case**: Synonyms and related terms
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### NOT
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Exclude terms:
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```
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cancer NOT review
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diabetes NOT animal
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"machine learning" NOT "deep learning"
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```
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**Caution**: May exclude relevant papers that mention both terms.
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### Combining Operators
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Use parentheses for complex logic:
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```
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(diabetes OR "diabetes mellitus") AND (treatment OR therapy)
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("CRISPR" OR "gene editing") AND ("therapeutic" OR "therapy")
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AND 2020:2024[Publication Date]
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(cancer OR neoplasm) AND (immunotherapy OR "immune checkpoint inhibitor")
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AND ("clinical trial"[Publication Type] OR "randomized controlled trial"[Publication Type])
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```
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## Advanced Search Builder
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**Access**: https://pubmed.ncbi.nlm.nih.gov/advanced/
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**Features**:
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- Visual query builder
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- Add multiple query boxes
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- Select field tags from dropdowns
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- Combine with AND/OR/NOT
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- Preview results
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- Shows final query string
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- Save queries
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**Workflow**:
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1. Add search terms in separate boxes
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2. Select field tags
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3. Choose Boolean operators
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4. Preview results
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5. Refine as needed
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6. Copy final query string
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7. Use in scripts or save
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**Example built query**:
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```
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#1: "Diabetes Mellitus, Type 2"[MeSH]
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#2: "Metformin"[MeSH]
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#3: "Clinical Trial"[Publication Type]
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#4: 2020:2024[Publication Date]
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#5: #1 AND #2 AND #3 AND #4
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```
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## Filters and Limits
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### Article Types
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||||
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||||
```
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"Review"[Publication Type]
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"Systematic Review"[Publication Type]
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"Meta-Analysis"[Publication Type]
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"Clinical Trial"[Publication Type]
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"Randomized Controlled Trial"[Publication Type]
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"Case Reports"[Publication Type]
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"Comparative Study"[Publication Type]
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||||
```
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|
||||
### Species
|
||||
|
||||
```
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humans[MeSH Terms]
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mice[MeSH Terms]
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rats[MeSH Terms]
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```
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|
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### Sex
|
||||
|
||||
```
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"Female"[MeSH Terms]
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"Male"[MeSH Terms]
|
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```
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### Age Groups
|
||||
|
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```
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"Infant"[MeSH Terms]
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"Child"[MeSH Terms]
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||||
"Adolescent"[MeSH Terms]
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"Adult"[MeSH Terms]
|
||||
"Aged"[MeSH Terms]
|
||||
"Aged, 80 and over"[MeSH Terms]
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```
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### Text Availability
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```
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free full text[Filter] # Free full-text available
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```
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||||
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### Journal Categories
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```
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"Journal Article"[Publication Type]
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```
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## E-utilities API
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NCBI provides programmatic access via E-utilities (Entrez Programming Utilities).
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### Overview
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**Base URL**: `https://eutils.ncbi.nlm.nih.gov/entrez/eutils/`
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**Main Tools**:
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- **ESearch**: Search and retrieve PMIDs
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- **EFetch**: Retrieve full records
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- **ESummary**: Retrieve document summaries
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- **ELink**: Find related articles
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- **EInfo**: Database statistics
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**No API key required**, but recommended for:
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- Higher rate limits (10/sec vs 3/sec)
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- Better performance
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- Identify your project
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|
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**Get API key**: https://www.ncbi.nlm.nih.gov/account/
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### ESearch - Search PubMed
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Retrieve PMIDs for a query.
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**Endpoint**: `/esearch.fcgi`
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**Parameters**:
|
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- `db`: Database (pubmed)
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- `term`: Search query
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- `retmax`: Maximum results (default 20, max 10000)
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- `retstart`: Starting position (for pagination)
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- `sort`: Sort order (relevance, pub_date, author)
|
||||
- `api_key`: Your API key (optional but recommended)
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**Example URL**:
|
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```
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https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?
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db=pubmed&
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term=diabetes+AND+treatment&
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retmax=100&
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retmode=json&
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api_key=YOUR_API_KEY
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```
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**Response**:
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```json
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{
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"esearchresult": {
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"count": "250000",
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"retmax": "100",
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"idlist": ["12345678", "12345679", ...]
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}
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}
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```
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### EFetch - Retrieve Records
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Get full metadata for PMIDs.
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**Endpoint**: `/efetch.fcgi`
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**Parameters**:
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- `db`: Database (pubmed)
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- `id`: Comma-separated PMIDs
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- `retmode`: Format (xml, json, text)
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- `rettype`: Type (abstract, medline, full)
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- `api_key`: Your API key
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||||
|
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**Example URL**:
|
||||
```
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https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?
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db=pubmed&
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id=12345678,12345679&
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retmode=xml&
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api_key=YOUR_API_KEY
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```
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|
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**Response**: XML with complete metadata including:
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- Title
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||||
- Authors (with affiliations)
|
||||
- Abstract
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||||
- Journal
|
||||
- Publication date
|
||||
- DOI
|
||||
- PMID, PMCID
|
||||
- MeSH terms
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||||
- Keywords
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||||
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||||
### ESummary - Get Summaries
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||||
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Lighter-weight alternative to EFetch.
|
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|
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**Example**:
|
||||
```
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||||
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi?
|
||||
db=pubmed&
|
||||
id=12345678&
|
||||
retmode=json&
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||||
api_key=YOUR_API_KEY
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```
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||||
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||||
**Returns**: Key metadata without full abstract and details.
|
||||
|
||||
### ELink - Find Related Articles
|
||||
|
||||
Find related articles or links to other databases.
|
||||
|
||||
**Example**:
|
||||
```
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https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?
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||||
dbfrom=pubmed&
|
||||
db=pubmed&
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||||
id=12345678&
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||||
linkname=pubmed_pubmed_citedin
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||||
```
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||||
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||||
**Link types**:
|
||||
- `pubmed_pubmed`: Related articles
|
||||
- `pubmed_pubmed_citedin`: Papers citing this article
|
||||
- `pubmed_pmc`: PMC full-text versions
|
||||
- `pubmed_protein`: Related protein records
|
||||
|
||||
### Rate Limiting
|
||||
|
||||
**Without API key**:
|
||||
- 3 requests per second
|
||||
- Block if exceeded
|
||||
|
||||
**With API key**:
|
||||
- 10 requests per second
|
||||
- Better for programmatic access
|
||||
|
||||
**Best practice**:
|
||||
```python
|
||||
import time
|
||||
time.sleep(0.34) # ~3 requests/second
|
||||
# or
|
||||
time.sleep(0.11) # ~10 requests/second with API key
|
||||
```
|
||||
|
||||
### API Key Usage
|
||||
|
||||
**Get API key**:
|
||||
1. Create NCBI account: https://www.ncbi.nlm.nih.gov/account/
|
||||
2. Settings → API Key Management
|
||||
3. Create new API key
|
||||
4. Copy key
|
||||
|
||||
**Use in requests**:
|
||||
```
|
||||
&api_key=YOUR_API_KEY_HERE
|
||||
```
|
||||
|
||||
**Store securely**:
|
||||
```bash
|
||||
# In environment variable
|
||||
export NCBI_API_KEY="your_key_here"
|
||||
|
||||
# In script
|
||||
import os
|
||||
api_key = os.getenv('NCBI_API_KEY')
|
||||
```
|
||||
|
||||
## Search Strategies
|
||||
|
||||
### Comprehensive Systematic Search
|
||||
|
||||
For systematic reviews and meta-analyses:
|
||||
|
||||
```
|
||||
# 1. Identify key concepts
|
||||
Concept 1: Diabetes
|
||||
Concept 2: Treatment
|
||||
Concept 3: Outcomes
|
||||
|
||||
# 2. Find MeSH terms and synonyms
|
||||
Concept 1: "Diabetes Mellitus"[MeSH] OR diabetes OR diabetic
|
||||
Concept 2: "Drug Therapy"[MeSH] OR treatment OR therapy OR medication
|
||||
Concept 3: "Treatment Outcome"[MeSH] OR outcome OR efficacy OR effectiveness
|
||||
|
||||
# 3. Combine with AND
|
||||
("Diabetes Mellitus"[MeSH] OR diabetes OR diabetic)
|
||||
AND ("Drug Therapy"[MeSH] OR treatment OR therapy OR medication)
|
||||
AND ("Treatment Outcome"[MeSH] OR outcome OR efficacy OR effectiveness)
|
||||
|
||||
# 4. Add filters
|
||||
AND 2015:2024[Publication Date]
|
||||
AND ("Clinical Trial"[Publication Type] OR "Randomized Controlled Trial"[Publication Type])
|
||||
AND English[Language]
|
||||
AND humans[MeSH Terms]
|
||||
```
|
||||
|
||||
### Finding Clinical Trials
|
||||
|
||||
```
|
||||
# Specific disease + clinical trials
|
||||
"Alzheimer Disease"[MeSH]
|
||||
AND ("Clinical Trial"[Publication Type]
|
||||
OR "Randomized Controlled Trial"[Publication Type])
|
||||
AND 2020:2024[Publication Date]
|
||||
|
||||
# Specific drug trials
|
||||
"Metformin"[MeSH]
|
||||
AND "Diabetes Mellitus, Type 2"[MeSH]
|
||||
AND "Randomized Controlled Trial"[Publication Type]
|
||||
```
|
||||
|
||||
### Finding Reviews
|
||||
|
||||
```
|
||||
# Systematic reviews on topic
|
||||
"CRISPR-Cas Systems"[MeSH]
|
||||
AND ("Systematic Review"[Publication Type] OR "Meta-Analysis"[Publication Type])
|
||||
|
||||
# Reviews in high-impact journals
|
||||
cancer immunotherapy
|
||||
AND "Review"[Publication Type]
|
||||
AND ("Nature"[Journal] OR "Science"[Journal] OR "Cell"[Journal])
|
||||
```
|
||||
|
||||
### Finding Recent Papers
|
||||
|
||||
```
|
||||
# Papers from last year
|
||||
"machine learning"[Title/Abstract]
|
||||
AND "drug discovery"[Title/Abstract]
|
||||
AND 2024[Publication Date]
|
||||
|
||||
# Recent papers in specific journal
|
||||
"CRISPR"[Title/Abstract]
|
||||
AND "Nature"[Journal]
|
||||
AND 2023:2024[Publication Date]
|
||||
```
|
||||
|
||||
### Author Tracking
|
||||
|
||||
```
|
||||
# Specific author's recent work
|
||||
"Doudna JA"[Author] AND 2020:2024[Publication Date]
|
||||
|
||||
# Author + topic
|
||||
"Church GM"[Author] AND "synthetic biology"[Title/Abstract]
|
||||
```
|
||||
|
||||
### High-Quality Evidence
|
||||
|
||||
```
|
||||
# Meta-analyses and systematic reviews
|
||||
(diabetes OR "diabetes mellitus")
|
||||
AND (treatment OR therapy)
|
||||
AND ("Meta-Analysis"[Publication Type] OR "Systematic Review"[Publication Type])
|
||||
|
||||
# RCTs only
|
||||
cancer immunotherapy
|
||||
AND "Randomized Controlled Trial"[Publication Type]
|
||||
AND 2020:2024[Publication Date]
|
||||
```
|
||||
|
||||
## Script Integration
|
||||
|
||||
### search_pubmed.py Usage
|
||||
|
||||
**Basic search**:
|
||||
```bash
|
||||
python scripts/search_pubmed.py "diabetes treatment"
|
||||
```
|
||||
|
||||
**With MeSH terms**:
|
||||
```bash
|
||||
python scripts/search_pubmed.py \
|
||||
--query '"Diabetes Mellitus"[MeSH] AND "Drug Therapy"[MeSH]'
|
||||
```
|
||||
|
||||
**Date range filter**:
|
||||
```bash
|
||||
python scripts/search_pubmed.py "CRISPR" \
|
||||
--date-start 2020-01-01 \
|
||||
--date-end 2024-12-31 \
|
||||
--limit 200
|
||||
```
|
||||
|
||||
**Publication type filter**:
|
||||
```bash
|
||||
python scripts/search_pubmed.py "cancer immunotherapy" \
|
||||
--publication-types "Clinical Trial,Randomized Controlled Trial" \
|
||||
--limit 100
|
||||
```
|
||||
|
||||
**Export to BibTeX**:
|
||||
```bash
|
||||
python scripts/search_pubmed.py "Alzheimer's disease" \
|
||||
--limit 100 \
|
||||
--format bibtex \
|
||||
--output alzheimers.bib
|
||||
```
|
||||
|
||||
**Complex query from file**:
|
||||
```bash
|
||||
# Save complex query in query.txt
|
||||
cat > query.txt << 'EOF'
|
||||
("Diabetes Mellitus, Type 2"[MeSH] OR "diabetes"[Title/Abstract])
|
||||
AND ("Metformin"[MeSH] OR "metformin"[Title/Abstract])
|
||||
AND "Randomized Controlled Trial"[Publication Type]
|
||||
AND 2015:2024[Publication Date]
|
||||
AND English[Language]
|
||||
EOF
|
||||
|
||||
# Run search
|
||||
python scripts/search_pubmed.py --query-file query.txt --limit 500
|
||||
```
|
||||
|
||||
### Batch Searches
|
||||
|
||||
```bash
|
||||
# Search multiple topics
|
||||
TOPICS=("diabetes treatment" "cancer immunotherapy" "CRISPR gene editing")
|
||||
|
||||
for topic in "${TOPICS[@]}"; do
|
||||
python scripts/search_pubmed.py "$topic" \
|
||||
--limit 100 \
|
||||
--output "${topic// /_}.json"
|
||||
sleep 1
|
||||
done
|
||||
```
|
||||
|
||||
### Extract Metadata
|
||||
|
||||
```bash
|
||||
# Search returns PMIDs
|
||||
python scripts/search_pubmed.py "topic" --output results.json
|
||||
|
||||
# Extract full metadata
|
||||
python scripts/extract_metadata.py \
|
||||
--input results.json \
|
||||
--output references.bib
|
||||
```
|
||||
|
||||
## Tips and Best Practices
|
||||
|
||||
### Search Construction
|
||||
|
||||
1. **Start with MeSH terms**:
|
||||
- Use MeSH Browser to find correct terms
|
||||
- More precise than keyword search
|
||||
- Captures all papers on topic regardless of terminology
|
||||
|
||||
2. **Include text word variants**:
|
||||
```
|
||||
# Better coverage
|
||||
("Diabetes Mellitus"[MeSH] OR diabetes OR diabetic)
|
||||
```
|
||||
|
||||
3. **Use field tags appropriately**:
|
||||
- `[MeSH]` for standardized concepts
|
||||
- `[Title/Abstract]` for specific terms
|
||||
- `[Author]` for known authors
|
||||
- `[Journal]` for specific venues
|
||||
|
||||
4. **Build incrementally**:
|
||||
```
|
||||
# Step 1: Basic search
|
||||
diabetes
|
||||
|
||||
# Step 2: Add specificity
|
||||
"Diabetes Mellitus, Type 2"[MeSH]
|
||||
|
||||
# Step 3: Add treatment
|
||||
"Diabetes Mellitus, Type 2"[MeSH] AND "Metformin"[MeSH]
|
||||
|
||||
# Step 4: Add study type
|
||||
"Diabetes Mellitus, Type 2"[MeSH] AND "Metformin"[MeSH]
|
||||
AND "Clinical Trial"[Publication Type]
|
||||
|
||||
# Step 5: Add date range
|
||||
... AND 2020:2024[Publication Date]
|
||||
```
|
||||
|
||||
### Optimizing Results
|
||||
|
||||
1. **Too many results**: Add filters
|
||||
- Restrict publication type
|
||||
- Narrow date range
|
||||
- Add more specific MeSH terms
|
||||
- Use Major Topic: `[MeSH Major Topic]`
|
||||
|
||||
2. **Too few results**: Broaden search
|
||||
- Remove restrictive filters
|
||||
- Use OR for synonyms
|
||||
- Expand date range
|
||||
- Use MeSH explosion (default)
|
||||
|
||||
3. **Irrelevant results**: Refine terms
|
||||
- Use more specific MeSH terms
|
||||
- Add exclusions with NOT
|
||||
- Use Title field instead of all fields
|
||||
- Add MeSH subheadings
|
||||
|
||||
### Quality Control
|
||||
|
||||
1. **Document search strategy**:
|
||||
- Save exact query string
|
||||
- Record search date
|
||||
- Note number of results
|
||||
- Save filters used
|
||||
|
||||
2. **Export systematically**:
|
||||
- Use consistent file naming
|
||||
- Export to JSON for flexibility
|
||||
- Convert to BibTeX as needed
|
||||
- Keep original search results
|
||||
|
||||
3. **Validate retrieved citations**:
|
||||
```bash
|
||||
python scripts/validate_citations.py pubmed_results.bib
|
||||
```
|
||||
|
||||
### Staying Current
|
||||
|
||||
1. **Set up search alerts**:
|
||||
- PubMed → Save search
|
||||
- Receive email updates
|
||||
- Daily, weekly, or monthly
|
||||
|
||||
2. **Track specific journals**:
|
||||
```
|
||||
"Nature"[Journal] AND CRISPR[Title]
|
||||
```
|
||||
|
||||
3. **Follow key authors**:
|
||||
```
|
||||
"Church GM"[Author]
|
||||
```
|
||||
|
||||
## Common Issues and Solutions
|
||||
|
||||
### Issue: MeSH Term Not Found
|
||||
|
||||
**Solution**:
|
||||
- Check spelling
|
||||
- Use MeSH Browser
|
||||
- Try related terms
|
||||
- Use text word search as fallback
|
||||
|
||||
### Issue: Zero Results
|
||||
|
||||
**Solution**:
|
||||
- Remove filters
|
||||
- Check query syntax
|
||||
- Use OR for broader search
|
||||
- Try synonyms
|
||||
|
||||
### Issue: Poor Quality Results
|
||||
|
||||
**Solution**:
|
||||
- Add publication type filters
|
||||
- Restrict to recent years
|
||||
- Use MeSH Major Topic
|
||||
- Filter by journal quality
|
||||
|
||||
### Issue: Duplicates from Different Sources
|
||||
|
||||
**Solution**:
|
||||
```bash
|
||||
python scripts/format_bibtex.py results.bib \
|
||||
--deduplicate \
|
||||
--output clean.bib
|
||||
```
|
||||
|
||||
### Issue: API Rate Limiting
|
||||
|
||||
**Solution**:
|
||||
- Get API key (increases limit to 10/sec)
|
||||
- Add delays in scripts
|
||||
- Process in batches
|
||||
- Use off-peak hours
|
||||
|
||||
## Summary
|
||||
|
||||
PubMed provides authoritative biomedical literature search:
|
||||
|
||||
✓ **Curated content**: MeSH indexing, quality control
|
||||
✓ **Precise search**: Field tags, MeSH terms, filters
|
||||
✓ **Programmatic access**: E-utilities API
|
||||
✓ **Free access**: No subscription required
|
||||
✓ **Comprehensive**: 35M+ citations, daily updates
|
||||
|
||||
Key strategies:
|
||||
- Use MeSH terms for precise searching
|
||||
- Combine with text words for comprehensive coverage
|
||||
- Apply appropriate field tags
|
||||
- Filter by publication type and date
|
||||
- Use E-utilities API for automation
|
||||
- Document search strategy for reproducibility
|
||||
|
||||
For broader coverage across disciplines, complement with Google Scholar.
|
||||
|
||||
Reference in New Issue
Block a user