literature-pulse

You can monitor bio-pharma papers by automating data retrieval from PubMed and Europe PMC. This Skill fetches recent literature, summarizes the papers using AI, and identifies key opinion leaders to streamline evidence synthesis for systematic reviews.

Yes, you can identify key opinion leaders automatically from PubMed search results. The Skill analyzes author frequency and impact factor from retrieved bio-pharma papers to highlight top researchers in your target field.

You can summarize bio-pharma literature using AI by processing retrieved PubMed records with Gemini or Claude. The Skill generates concise AI summarizations of bio-pharma papers, providing both Korean and English summaries for evidence synthesis.

Yes, biopython works with Europe PMC for systematic review data retrieval. This Skill uses biopython alongside requests and json dependencies to query APIs, fetch bio-pharma literature, and structure the data for AI summarization and KOL identification.

The best way to track NASH research papers is to query PubMed and Europe PMC using targeted keywords. This Skill retrieves NASH literature, summarizes the findings with AI, and ranks key opinion leaders based on author frequency and impact factor.

AI summarization for systematic reviews depends on the quality of retrieved PubMed and Europe PMC records. While it accelerates evidence synthesis by summarizing bio-pharma papers, users must verify AI outputs against original literature to ensure research accuracy.