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Connected Papers: should researchers use it?

A citation graph tool for understanding nearby papers, influential prior work, and connected research clusters.

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Before using this in research

The goal is not to adopt another tool. The goal is to reduce verified research time without weakening the evidence trail.

Best for

Medical students, clinical researchers, residents, PIs, and review authors who need to find relevant papers without losing search reproducibility.

First step

Write the research question in PICO or PECO form, then list synonyms before opening any AI search tool.

A safer workflow

  1. 1Create a baseline query in PubMed, Embase, Web of Science, or another trusted bibliographic database.
  2. 2Use AI search tools to expand terms, identify seed papers, and discover related work.
  3. 3Trace key papers through references, citations, and similar-paper networks.
  4. 4Record databases, dates, query strings, inclusion logic, and papers that require full-text review.

Watch-outs

  • AI literature tools can miss important papers and may not provide a reproducible search strategy.
  • A novelty check is not the same as a formal institutional literature search.
  • Claims for manuscripts or grants still need database search records and source verification.

Evidence checks

  • Can every important claim be traced to PMID, DOI, or a journal page?
  • Did you keep the exact search string and search date?
  • Did you compare AI-discovered papers against at least one structured database query?

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