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HALOWERK buerowerk – Clinical Symptom Literals Source Note Register
x402
HALOWERK buerowerk – Clinical Symptom Literals Source Note Register is a paid API for AI agents from buero.halowerk.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-22).
Analyzes meeting transcript segments to extract and register clinical symptom literals and source notes from medical or clinical discussions.
Price / call$0.01
Success—
StatusUnknown
How this service works
HALOWERK buerowerk — bezahlte Endpunkte nach x402. Preise in USDC auf Base Mainnet.
Output
A JSON object containing extracted clinical symptom literals and associated source notes registered from the input transcript segments, structured for clinical documentation purposes.
Example use cases
Post-consultation symptom extraction
“I just got the transcript from a 30-minute patient consultation with two speakers — can you run it through to pull out every clinical symptom that was mentioned and register them with their source notes?”
Clinical case conference documentation
“We recorded a 90-minute clinical case conference and have the full transcript with speaker labels and timestamps. Can you extract all the symptom literals that were discussed so we can build a structured register?”
Telehealth session symptom logging
“Here's the transcript from a telehealth session — about 20 minutes long, one doctor and one patient. Please identify and register every clinical symptom or complaint the patient described during the call.”
Technical details
Endpoint
POSThttps://buero.halowerk.com/v1/baumarkt/meeting/clinical-symptom-literals-source-note-register?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to automatically extract and register clinical symptom mentions from transcribed medical meetings or consultations. It is purpose-built for clinical NLP on structured transcript data with speaker-attributed segments, making it ideal for healthcare documentation workflows where manual symptom logging from recordings is too time-consuming.
Side effects
- Empty or missing segments array returns validation error
- Segment text exceeding 3000 characters per cue is rejected
- Duration exceeding 1800 seconds in transcript_package is rejected
- Missing required fields (start, end, text) in segments causes schema validation failure
- Non-medical or ambiguous text may yield no symptom extractions
- Speaker field null values are accepted but may reduce attribution accuracy
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| segments | array | |
| transcript_package | object |
Output
Schema · Response
{
"type": "json"
}Tags
x402
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