SciSpace Academy

Level: Intermediate · 6 lessons

Systematic Review with AI in 6 Lessons (PRISMA-Ready)

A structured route through a full systematic review: from planning and PRISMA-ready screening to evidence synthesis, a real case study and running reviews as a team.

Start lesson 1

Lessons

  1. How to Conduct a Systematic Literature Review with AI: Complete WorkflowEN35 min
    Lesson 1Tutorial

    How to Conduct a Systematic Literature Review with AI: Complete Workflow

    A systematic review in SciSpace can use AI assistance, but it must remain protocol-driven and reproducible. Define eligibility, outcomes, sources, dates, and synthesis methods before searching; document every query and screening decision; extract the same fields from each included study; assess quality; and preserve the evidence trail needed to reconstruct the review.

  2. How to Conduct a PRISMA-Ready Systematic Literature Review with AIEN
    Lesson 2Tutorial

    How to Conduct a PRISMA-Ready Systematic Literature Review with AI

    In SciSpace, a PRISMA-ready review is one whose search, screening, exclusions, extraction, appraisal, and synthesis can be reconstructed. Save every database strategy, retain record counts and exclusion reasons, apply a protocol consistently, and verify that the final report aligns with the PRISMA checklist and flow diagram.

  3. AI-Assisted Rapid Reviews and Evidence Synthesis with SciSpaceEN
    Lesson 3Tutorial

    AI-Assisted Rapid Reviews and Evidence Synthesis with SciSpace

    Use SciSpace to support a rapid review by narrowing scope and streamlining methods—not by hiding shortcuts. Agree on the question, timeframe, stakeholders, and minimum evidence standard; document restricted searches and screening decisions; extract consistently; and state what the accelerated method may have missed.

  4. A Systematic Review Example: From Protocol to Synthesis with SciSpaceEN
    Lesson 4Tutorial

    A Systematic Review Example: From Protocol to Synthesis with SciSpace

    Use this SciSpace case study to see how a systematic review changes when real records expose ambiguous criteria, missing synonyms, and borderline decisions. Recreate the protocol, pilot screening, extraction, quality appraisal, and synthesis, then compare each decision with the video rationale rather than copying the final output.

  5. How to Conduct a Systematic Literature Review with SciSpace: Team DemoEN
    Lesson 5Tutorial

    How to Conduct a Systematic Literature Review with SciSpace: Team Demo

    SciSpace can automate much of the operational work of a systematic review while preserving researcher approval at critical stages. The workflow records the research questions, inclusion and exclusion criteria, database-specific search queries, screening decisions, extracted evidence, PRISMA flow diagram, and final structured report so the review remains traceable.

  6. Using SciSpace Responsibly: Trust, Evidence and AI in ResearchEN
    Lesson 6Tutorial

    Using SciSpace Responsibly: Trust, Evidence and AI in Research

    When SciSpace generates a research answer, verify it by separating extracted evidence, synthesis, inference, recommendation, and unknowns. Open the supporting sources, confirm that each exists and supports the claim, check methods and numbers, compare contradictory evidence, and label uncertainty before using the answer in research or decisions.

Try this on SciSpace

Use case: Systematic review