Literature Search
Automated citation chasing, API wrappers for PubMed, and search strategy testing.
Curated List / Directory
Awesome Evidence Synthesis: Open Source Systematic Review Tools
Systematic methods for identifying, evaluating, and integrating research evidence across studies. A curated directory of 200+ open-source software tools, libraries, and frameworks designed to support the systematic review, meta-analysis, and evidence synthesis workflow.
Explore by Category
Tools are curated across every stage of the systematic review process.
Text Mining & NLP
Semantic annotation, sentiment analysis, and concept extraction using ML.
Screening
AI-assisted screening, machine learning prioritization, and deduplication.
Data Extraction & Cleaning
PDF parsing, table extraction, OCR tools, and plot digitizers.
Risk of Bias Assessment
Automated assessment tools and visualization for bias (ROB2, QUADAS, etc.).
Reference Management
Open-source bibliography managers and citation cleaning tools.
Workflow & Automation
Tools for reproducible reporting, document conversion, and project management.
Visualization & Reporting
Forest plots, funnel plots, network graphs, and evidence mapping.
Meta-analysis
Statistical packages for R and Python, Network Meta-analysis, and Bayesian models.
Statistics
P-value combination, robust variance estimation, and error control in meta-analysis.
Criteria & Policies
Inclusion Criteria: Tools must use a recognized open-source license (e.g., MIT, GPL), have a public code repository, be non-proprietary, be reusable/extensible, and be relevant to evidence synthesis.
External API Policy: Tools interacting with external APIs are included if they use an OSI-approved license, have public code, use external services only for data access/integration, and do not rely on hidden proprietary logic.
Open source ensures full transparency in research, allowing scientists to inspect algorithms, avoid "black box" pitfalls, and build upon existing work to accelerate innovation in evidence synthesis.