LitStudy: Using the power of Python to automate scientific literature analysis from the comfort of a Jupyter notebook
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Updated
May 27, 2025 - Python
LitStudy: Using the power of Python to automate scientific literature analysis from the comfort of a Jupyter notebook
Organize literature into ideas, fast.
An AI Tool for Automated Research Question and Hypothesis Generation from a given Scientific Literature
Multi-agent workflow for accurate and comprehensive literature reviews in philosophy
Semi-automatic Literature Survey (SaLS)
A text mining tool for developing visual and interactive relationship networks from PubMed article information.
An AI research assistant that helps you rank, compare, and follow up on papers — so you can decide what to read next
A template to create your own literature survey engine
Bibby is your LateX Research writing friend, Write research papers faster, do more research output.
A Decision Support System for Document Retrieval and Study Selection in the Systematic Literature Review Process
Node.js Electron GUI for Scraping the Google Play Store.
Simple tool created with Microsoft Excel (365) to cluster subtopics in references in a literature survey for a paper, thesis or any other academic work,
This tool allows to peform a comprehensive and systematic literature review of any research domain. The code allows scraping data from the Scopus database, storing them in GCP Datastore, and then running the community detection and analysis locally.
AI-assisted systematic literature review skill. PRISMA 2020-compliant workflow with automated multi-database retrieval, 100% human audit, independent dual screening, active learning calibration, and tamper-evident audit logging. No coding experience required
The frontend of the DaWeSearch project
The backend of the DaWeSearch project - a tool to conduct structured literature reviews (SLR).
The prospective search engine is a search engine for classical literature, the search engine uses TF-IDF vectorisation and cosine similarity, processing and indexing 316,000 tokens across 7 classic novels with sub-0.1 second query times.
this contains a file which was used to filter authors from a pubmed search for a systematic review based on the location of the author (requiring 50% USA led) and that one author from the USA was an academic
Promoting Serendipitous Discovery of Academic Literature with Transformers & Visual Analytics
Local scholarly metadata harvesting and notebook-based analysis app for literature reviews across PubMed, Europe PMC, OpenAlex, Crossref, Semantic Scholar, Scopus, and more.
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