Axelium vs SWIFT-Review

Axelium is an AI-assisted platform for systematic reviews and meta-analyses, spanning evidence search, screening, analysis, reporting, and living reviews. Its 11 stages include protocol, search, screening, full-text review, extraction, RoB 2.0, GRADE, statistics, network meta-analysis, reporting, and living reviews. The maker says AI extracts structured values while deterministic code calculates statistics, and data points link to snippets in original PDFs. Listed methods include pairwise and network synthesis, Cochrane RoB 2.0, GRADE certainty ratings, CERQual, and PRISMA-style reporting. It imports references from tools and databases including EndNote, Zotero, PubMed, ClinicalTrials.gov, and Web of Science; exports include DOCX, XLSX, RIS, BibTeX, and RevMan. Team controls include roles, comments, dual-person sign-off, conflict adjudication, and versioned audit snapshots. A free plan includes one lifetime review and one seat; Researcher costs $29 a month. Human validation is needed for screening suggestions, extracted values, risk-of-bias assessments, and draft reports. Recurring statistical refresh for living-review network meta-analysis is paused, though scheduled cycles can import, screen, and extract new evidence.

SWIFT-Review is a desktop workbench for formulating systematic reviews and prioritizing literature for screening. Statistical text mining and machine learning identify over-represented topics and rank documents for manual review. Users can search, categorize, prioritize, visualize, and extract information from large citation sets. The ranking workflow requires an initial training seed, and the software does not estimate how many relevant articles remain above a threshold. It can import PubMed IDs or XML, RIS files, and previously saved SWIFT Text-mining Project files; PMID imports retrieve citation data through NLM’s Entrez e-Utilities interface. Exports include Excel, RIS, and plain tab-delimited text. The free desktop software is available for Windows and Mac, with downloads through Sciome’s applications portal after signing in or creating a free account. Installation requires administrative access. The guide lists 64-bit Windows 7, 8, or 10 and 64-bit Mac OS X 10.8 or later, and recommends 8 GB RAM; very large projects may need more. Minor updates usually happen automatically, while major updates may require administrator privileges.