Aims, scope, and publishing model

SAIMSARA Journal is an experimental project created to address the rapid growth of scientific evidence in medicine and life sciences and the limitations of human-written reviews and meta-analyses. Articles are generated by an AI RAG workflow that searches and extracts literature from three major libraries: Semantic Scholar (~230M papers), Europe PMC (~45M papers), and PubMed (~39M papers).

Each review follows a PRISMA-style screening workflow and includes outcome-oriented synthesis (beneficial, harmful, or no clear effect), weighted by study sample size. References are transparent and traceable. Issues then curate domain collections and power a dedicated AI RAG chatbot for interactive Q&A on the issue topic.

Articles are released Online First. Each registered SAIMSARA user can publish a generated article from their account. Published articles are reviewed by the Editor-in-Chief and curated into topic-specific domain issues. Each issue powers an interactive AI RAG chatbot that everyone can use for Q&A.

SAIMSARA Journal publishes machine-generated syntheses with human editorial oversight. The goal is reproducibility, traceability, and rapid updating.