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PubMed Trending Subtopics Analyzer
x402
PubMed Trending Subtopics Analyzer is a paid API for AI agents from pubmed.sekgen.xyz, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-13).
Identifies and ranks the fastest-growing biomedical sub-topics within a research field using multi-year publication growth analysis from PubMed
Price / call$0.05
Success—
StatusUnknown
How this service works
Discover which biomedical sub-topics within a research field are growing fastest — multi-year growth analysis for clinical, pharmaceutical, genomics, and scientific domains
Output
A ranked list of biomedical sub-topics within the queried research field, ordered by growth rate, with multi-year publication counts, CAGR values, and trend signals indicating which niches are accelerating fastest.
Example use cases
Example prompt
“Which sub-topics within CRISPR gene editing research are growing fastest right now — give me the multi-year growth breakdown so I can see where the field is accelerating?”
Technical details
Endpoint
GEThttps://pubmed.sekgen.xyz/api/v1/trending-subtopicsWhen to prefer
Use this endpoint when you need to understand the internal landscape of a research field — specifically which sub-areas are growing fastest over multiple years. Prefer this over single-topic trend endpoints when you want comparative subtopic intelligence within a domain, or over the emerging-topics scanner when you want depth within one field rather than breadth across domains.
Side effects
- Empty or overly broad query returns no meaningful sub-topic differentiation
- Highly niche topic with sparse PubMed coverage may return unreliable growth rates
- Rate limiting or payment failure returns 402 error requiring x402 micropayment
- Query terms not recognized in PubMed MeSH taxonomy may yield unexpected subtopic groupings
- Network timeout if PubMed upstream is slow
Input
{
"input": {
"type": "http",
"method": "GET",
"queryParams": {
"query": "oncology"
}
}
}Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
{
"as_of": "2026-05-29",
"query": "oncology",
"cached": false,
"results": [
{
"cagr": 0.607,
"counts": {
"2023": 783,
"2024": 1276,
"2025": 2023
},
"topic_id": "T11636",
"topic_name": "Artificial Intelligence in Healthcare and Education",
"growth_score": 2.008,
"trend_direction": "growing",
"latest_year_count": 2023
},
{
"cagr": 0.472,
"counts": {
"2023": 251,
"2024": 410,
"2025": 544
},
"topic_id": "T12702",
"topic_name": "Brain Tumor Detection and Classification",
"growth_score": 1.292,
"trend_direction": "growing",
"latest_year_count": 544
},
{
"cagr": 0.423,
"counts": {
"2023": 166,
"2024": 219,
"2025": 336
},
"topic_id": "T13702",
"topic_name": "Machine Learning in Healthcare",
"growth_score": 1.068,
"trend_direction": "growing",
"latest_year_count": 336
},
{
"cagr": 0.383,
"counts": {
"2023": 159,
"2024": 305,
"2025": 304
},
"topic_id": "T11396",
"topic_name": "Artificial Intelligence in Healthcare",
"growth_score": 0.95,
"trend_direction": "growing",
"latest_year_count": 304
},
{
"cagr": 0.314,
"counts": {
"2023": 248,
"2024": 350,
"2025": 428
},
"topic_id": "T13544",
"topic_name": "Women's cancer prevention and management",
"growth_score": 0.825,
"trend_direction": "growing",
"latest_year_count": 428
},
{
"cagr": 0.279,
"counts": {
"2023": 214,
"2024": 304,
"2025": 350
},
"topic_id": "T14423",
"topic_name": "Military Technology and Strategies",
"growth_score": 0.709,
"trend_direction": "growing",
"latest_year_count": 350
},
{
"cagr": 0.231,
"counts": {
"2023": 437,
"2024": 489,
"2025": 662
},
"topic_id": "T10063",
"topic_name": "Nanoparticle-Based Drug Delivery",
"growth_score": 0.651,
"trend_direction": "growing",
"latest_year_count": 662
},
{
"cagr": 0.182,
"counts": {
"2023": 812,
"2024": 861,
"2025": 1134
},
"topic_id": "T10862",
"topic_name": "AI in cancer detection",
"growth_score": 0.555,
"trend_direction": "growing",
"latest_year_count": 1134
},
{
"cagr": 0.217,
"counts": {
"2023": 226,
"2024": 230,
"2025": 335
},
"topic_id": "T10725",
"topic_name": "RNA Interference and Gene Delivery",
"growth_score": 0.549,
"trend_direction": "growing",
"latest_year_count": 335
},
{
"cagr": 0.176,
"counts": {
"2023": 539,
"2024": 520,
"2025": 745
},
"topic_id": "T10782",
"topic_name": "Nanoplatforms for cancer theranostics",
"growth_score": 0.505,
"trend_direction": "growing",
"latest_year_count": 745
}
],
"cache_date": "2026-05-29T22:35:19.931Z",
"window_years": 3,
"total_topics_found": 223
}Tags
x402
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