ASReview vs SyRF

ASReview is a free, open-source tool that uses AI-aided active learning to prioritize records for systematic review screening, with a human making screening decisions. Its site says the approach can reduce screening workload by up to 95%. Users can simulate AI-aided review to compare models, while Crowdscreen supports parallel screening with access managed by administrators through a private login system. The described model families are ELAS-Ultra, ELAS-Heavy, and language-agnostic ELAS-L; ELAS-Heavy and ELAS-L require the Dory package. ASReview works with reference managers including EndNote and PubMed, and imports and exports CSV, RIS, and XLSX files. Documentation includes a Python API, while the institutional workflow also describes a REST API and CLI for automation. In a local setup, data stays on the user's computer; server deployments keep it in the organization's environment and follow its policies. Support includes documentation, tutorials, videos, community discussion, and organizational workshops and consultancy. ASReview LAB costs nothing with no licensing fees or subscriptions, though running hardware or a server may incur costs.

SyRF is a web platform for researchers conducting systematic reviews and meta-analyses of preclinical studies. It supports collaborative projects, configurable workflows, study screening, annotation, data extraction, and educational guidance. By default, two reviewers assess studies against inclusion and exclusion criteria, with a third reviewer handling disagreements. Student projects can enable single screening, though the guide does not recommend it for journal-bound reviews. Administrators create annotation questions and assign them to workflow stages; graph extraction requires data extraction and annotation together. Studies and associated data, including quantitative results for analysis in R or SAS, can be downloaded. References must be deduplicated and supplied as EndNote Desktop XML or CSV. Full-text PDFs may be linked, but users provide the files separately for SyRF staff to process and store. Projects can be public or private, and each project currently supports one criteria set. SyRF is free online, with a minimum feature set under continuous development.