Precise, HIPAA-aware data pipelines for clinical NLP, diagnostic AI, and healthcare RAG systems. Automated PHI masking, clinical entity normalization, and human-verified delivery — so your AI meets the accuracy standards your patients and regulators demand.
Healthcare AI demands higher accuracy and stricter compliance than any other vertical. Our pipelines are designed for that standard.
Every extraction pipeline is designed with healthcare data handling standards in mind. Automated PHI detection and masking before any data leaves our systems.
Patient names, MRNs, dates of birth, and other Protected Health Information are automatically detected and redacted before dataset delivery.
Medical terminology resolved against SNOMED CT, ICD-10, and LOINC ontologies so your LLM receives standardized, unambiguous clinical concepts.
Discharge summaries, clinical notes, and EHR exports chunked and structured for optimal RAG retrieval and diagnostic NLP model performance.
From clinical decision support to medical coding automation, ScrapeZen delivers the structured data your healthcare AI needs to perform at a clinical standard.
// Sample normalized clinical record
{
"record_type": "clinical_note",
"date": "2026-03-15T09:30:00Z",
"diagnoses": [
{
"code": "ICD-10: J18.9",
"term": "Pneumonia, unspecified",
"snomed": "233604007"
}
],
"medications": [
{
"rxnorm": "723",
"name": "Amoxicillin",
"dose": "500mg",
"frequency": "TID"
}
],
"pii_masked": true,
"compliance": ["HIPAA", "GDPR"]
}ScrapeZen's healthcare pipelines are designed with HIPAA data handling standards in mind, including automated PHI detection and masking, access controls, and data minimisation principles. We recommend discussing a Business Associate Agreement (BAA) as part of your MSA for any production healthcare engagement.
Our normalization pipelines support entity resolution against SNOMED CT, ICD-10-CM, ICD-10-PCS, CPT, LOINC, and RxNorm. Custom ontology mappings can be scoped during your Proof of Concept.
ScrapeZen extracts and normalizes publicly available medical data sources — clinical literature, drug databases, medical coding references, and healthcare directories. EHR integrations involving patient records require a client-side secure data transfer arrangement and a signed BAA.
Request a free Proof of Concept — we'll extract, normalize, and deliver a representative healthcare dataset sample within 3 to 7 business days.
Request a Free Healthcare PoC