Use Case
Reduce a 40-page systematic review to a one-page actionable brief. Synthesise multiple papers, grey literature, and policy documents into structured summaries for decision-makers in a fraction of the time it normally takes.
Evidence synthesis is one of the most time-intensive tasks in public health, and one where AI provides genuinely significant time savings. By uploading documents or pasting text, you can ask AI to extract key findings, compare methodologies, identify gaps, and produce structured summaries tailored to your audience. Google's Notebook LM or Notebooks on Microsoft Copilot are particularly useful for this type of synthesis.
This is not a replacement for systematic review methodology (there are several AI tools designed to assist systematic reviews...more on that in a blog post coming soon). It is a tool for making existing evidence more accessible and actionable.
Upload a PDF or paste text and ask for a structured summary — key findings, methodology, limitations, and implications for policy or practice.
Paste in abstracts from several papers (or upload the PDFs) and ask AI to identify points of consensus, areas of disagreement, and gaps in the evidence.
Take a technical paper and ask for a plain-language version suitable for community health workers, local elected officials, or the general public.
Export notes and abstracts from Zotero as a text file and paste them into a conversation. Ask Claude to synthesise the collection into a structured literature overview.