Active learning for systematic reviews
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Updated
Jun 11, 2024 - Python
Active learning for systematic reviews
Papers informations from top AI conferences
Docker compose for setting up ASReview server with authentication
Workflow generator for simulation studies using the command line interface of ASReview LAB
Artwork for the ASReview project
This repository contains open teaching materials on using ASReview
Tool to preprocess datasets for ASReview
Tools such as plots and metrics to analyze (simulated) reviews for ASReview LAB
This plugin adds a new feature extractor based on doc2vec with a wider vector.
A model extension for ASReview. ASReview multilingual feature extractor is a feature extractor based on distiluse-base-multilingual-cased-v1.
An extension for ASReview Lab to preprocess the dataset before importing in ASReview
Extension for ASReview Lab for exporting notes from GUI to dataset csv file
ASReview Classifer Model Extension with ensemble classifiers
Extension for ASReview Lab for postprocessing the output of Screening
ASReview extension to generate wordcloud from data files.
The research archive accompanying my master thesis project
Project to examine if state-of-the-art feature extractors (i.e., transformers like RoBERTa, MPNET, and SPECTER) can outperform classical feature extractors (i.e., tf-idf and Doc2Vec) when classifying systematic reviews as relevant or irrelevant (using the ASReview software)
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