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PubMed Key Papers Scorer
x402
PubMed Key Papers Scorer is a paid API for AI agents from pubmed.sekgen.xyz, paid per call via x402, $0.03/call, status unknown (last checked 2026-09-13).
Retrieves and ranks key biomedical papers from PubMed scored by journal prestige, MeSH relevance, and clinical impact for literature review and drug discovery
Price / call$0.03
Success—
StatusUnknown
How this service works
Scored key biomedical papers from PubMed with citation metrics — ranked by journal prestige, MeSH relevance, and clinical impact for literature review and drug discovery research
Output
A ranked list of key biomedical papers from PubMed, each with scoring metadata including journal prestige score, MeSH relevance score, clinical impact score, citation counts, author information, publication year, and abstract — ordered to surface the most impactful literature for the queried topic.
Example use cases
Example prompt
“Pull the top scored key papers on KRAS-mutant non-small cell lung cancer from PubMed, ranked by journal prestige and clinical impact, so I can build a literature review.”
Technical details
Endpoint
GEThttps://pubmed.sekgen.xyz/api/v1/keypapersWhen to prefer
Use this endpoint when you need pre-scored, ranked biomedical literature rather than raw search results — especially for drug discovery pipelines, systematic literature reviews, or clinical evidence gathering where journal prestige and citation impact matter. Prefer over generic PubMed search when you need quality-ranked output rather than chronological or relevance-only ordering.
Side effects
- No papers found for overly narrow or misspelled query terms
- Rate limiting or payment failure returning 402 status
- Timeout if PubMed upstream API is slow or unavailable
- Empty result set for very new or niche research topics with limited PubMed coverage
Input
{
"input": {
"type": "http",
"method": "GET",
"queryParams": {
"query": "artificial intelligence"
}
}
}Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
{
"query": "artificial intelligence",
"cached": false,
"papers": [
{
"fwci": 3.0359,
"pmid": "38355097",
"score": 6,
"title": "Ethics and artificial intelligence",
"journal": "Rev Clin Esp (Barc)",
"pub_type": "review",
"pub_year": 2024,
"open_access": {
"url": null,
"status": "closed"
},
"cited_by_count": 28,
"score_breakdown": {
"top_journal": 0,
"relevance_rank": 2,
"citation_impact": 2,
"review_or_trial": 2,
"mesh_major_topic": 0,
"multi_strategy_hit": 0
},
"authors_enriched": [
{
"name": "Luis Inglada Galiana",
"country": "ES",
"institution": "Hospital Universitario Río Hortega"
},
{
"name": "Luís Corral-Gudino",
"country": "ES",
"institution": "Universidad de Valladolid"
},
{
"name": "P. Miramontes González",
"country": "ES",
"institution": "Universidad de Valladolid"
}
],
"citation_percentile": 0.91655451
},
{
"fwci": 3.3734,
"pmid": "38525882",
"score": 6,
"title": "Artificial intelligence to advance acute and intensive care medicine",
"journal": "Curr Opin Crit Care",
"pub_type": "review",
"pub_year": 2024,
"open_access": {
"url": "https://doi.org/10.1097/mcc.0000000000001150",
"status": "hybrid"
},
"cited_by_count": 32,
"score_breakdown": {
"top_journal": 0,
"relevance_rank": 2,
"citation_impact": 2,
"review_or_trial": 2,
"mesh_major_topic": 0,
"multi_strategy_hit": 0
},
"authors_enriched": [
{
"name": "Laurens A. Biesheuvel",
"country": "NL",
"institution": "Amsterdam University Medical Centers"
},
{
"name": "Dave A. Dongelmans",
"country": "NL",
"institution": "Amsterdam University Medical Centers"
},
{
"name": "Paul Elbers",
"country": "NL",
"institution": "Amsterdam University Medical Centers"
}
],
"citation_percentile": 0.92705279
},
{
"pmid": "42263727",
"score": 5,
"title": "Global advances in health artificial intelligence: a workforce imperative",
"journal": "Lancet",
"pub_type": "review",
"pub_year": 2026,
"score_breakdown": {
"top_journal": 3,
"relevance_rank": 0,
"review_or_trial": 2,
"mesh_major_topic": 0,
"multi_strategy_hit": 0
}
},
{
"fwci": 1.7623,
"pmid": "33242635",
"score": 4,
"title": "Artificial intelligence in cardiology",
"journal": "Trends Cardiovasc Med",
"pub_type": "review",
"pub_year": 2022,
"open_access": {
"url": null,
"status": "closed"
},
"cited_by_count": 92,
"score_breakdown": {
"top_journal": 0,
"relevance_rank": 1,
"citation_impact": 1,
"review_or_trial": 2,
"mesh_major_topic": 0,
"multi_strategy_hit": 0
},
"authors_enriched": [
{
"name": "Dipti Itchhaporia",
"country": "US",
"institution": "Hoag Memorial Hospital Presbyterian"
}
],
"citation_percentile": 0.86236236
},
{
"pmid": "42263121",
"score": 3,
"title": "Oxytocin selectively biases sensory-prefrontal communication through network-level suppression and theta coupling",
"journal": "Proc Natl Acad Sci U S A",
"pub_type": "research",
"pub_year": 2026,
"score_breakdown": {
"top_journal": 3,
"relevance_rank": 0,
"review_or_trial": 0,
"mesh_major_topic": 0,
"multi_strategy_hit": 0
}
},
{
"pmid": "42268453",
"score": 2,
"title": "Carbonic anhydrase VIII as a regulator of intracellular calcium signaling: mechanistic insights and implications in human disease",
"journal": "Mol Biol Rep",
"pub_type": "review",
"pub_year": 2026,
"score_breakdown": {
"top_journal": 0,
"relevance_rank": 0,
"review_or_trial": 2,
"mesh_major_topic": 0,
"multi_strategy_hit": 0
}
}
],
"partial": false,
"end_year": 2026,
"cache_date": "2026-06-11",
"start_year": 2021,
"strategies_completed": 3
}Tags
x402
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