systematic-literature-reviews

Active learning for systematic reviews

Parsifal is a tool to assist researchers to perform Systematic Literature Reviews

LitStudy: Using the power of Python to automate scientific literature analysis from the comfort of a Jupyter notebook

Systematic Literature Review (SLR) using AI involves leveraging artificial intelligence techniques to automate and expedite the process of reviewing and synthesizing large volumes of scholarly literature.

tools for fast reading of docs

Workflow generator for simulation studies using the command line interface of ASReview LAB

Tool to preprocess datasets for ASReview

Open Science AI Tools for Systematic, Protocol-Based Literature Reviews

[NeurIPS 2023] CSMeD: Bridging the Dataset Gap in Automated Citation Screening for Systematic Literature Reviews

Written in python, for checking reference lists in systematic reviews and literature reviews, helps with reference list searching both backward&forward by extracting references and creating search queries, ranks articles by relevance to improve screening efficiency, download full-text pdf of research articles in batch.

Artwork for the ASReview project

Awesome list of open-source tools for systematic reviews, meta-analysis, and evidence synthesis derived from Evidence Synthesis Tools Directory.

ASReview extension to generate wordcloud from data files.

Official extension for ASReview LAB enabling state-of-the-art NLP models with dense embeddings and deep learning architectures. Ideal for systematic reviews where lightweight models fall short.

Simulations for the https://github.com/asreview/asreview

slr-kit is a framework to support the analysis of scientific literature based on topic modeling, allowing to extract useful statistics

A very simple python script to generate bibtex files (.bib) from exported parsifal's xls spreadsheet.

Get related terms to a word.

Node.js Electron GUI for Scraping the Google Play Store.

A powerful, open-source tool for automating systematic literature reviews (SLRs) with support for +9 AI providers, reference ingestion, deduplication, two-stage screening, and structured data extraction.