Healthcare AI Data

Clinical Speech Data Collected by People Who Understand Medicine

Healthcare AI needs data from clinical environments with domain-specific vocabulary. YPAI recruits from 40,000+ vetted contributors across 150+ languages to collect clinical speech data that meets HIPAA, GDPR Article 9 biometric, and EU AI Act requirements.

Compliance HIPAA · GDPR · EU AI Act

Full regulatory coverage for clinical data. BAA available. De-identification built into every workflow.

Coverage 14+ European Languages

Clinical terminology corpora across major EU healthcare markets. Same protocols, multiple languages.

Contributors Healthcare Professionals

Physicians, nurses, radiologists, and medical linguists. Not crowd workers reading medical scripts.

Norwegian Jurisdiction | GDPR-Native | EU AI Act Ready | Zero CLOUD Act Exposure
Data Types

Healthcare Data That Reflects Clinical Reality

Four categories of clinical speech data, each collected by professionals with domain expertise. Every dataset includes provenance documentation and consent verification.

Clinical Dictation

Physician notes, discharge summaries, procedure documentation. Real medical vocabulary from practicing clinicians, not actors reading scripts. Collected in clinical settings with authentic ambient conditions.

Discharge summaries Progress notes Procedure reports

Patient-Provider Dialogue

Consultation recordings for conversational AI. Multiple specialties - primary care, cardiology, oncology, psychiatry. Turn-by-turn annotated with speaker roles and medical entities.

Medical Terminology Corpora

Specialized vocabulary datasets for medical NLP. Radiology, cardiology, pathology. Each term recorded with correct pronunciation by native-speaking clinicians.

Multilingual Clinical Data

Same clinical conditions, multiple European languages. For AI systems deployed across EU healthcare markets. Consistent recording protocols ensure cross-language comparability for model training and evaluation.

German French Norwegian Dutch + 10 more
Collection Process

From Protocol Design to Delivery

A six-phase process built for healthcare data. Every step includes compliance checkpoints and documentation that satisfies regulatory auditors.

Typical timeline: 8-16 weeks from protocol design to first delivery, depending on specialty requirements and language coverage.

01

Protocol Design

Collaborative protocol development with your clinical team. We define recording scenarios, speaker profiles, vocabulary targets, and quality thresholds before any data collection begins.

02

IRB & Ethics Review

We prepare and submit ethics board documentation. Experience with institutional review boards across EU and US jurisdictions. Consent forms, data handling agreements, and participant information sheets included.

03

Specialist Recruitment

Recruiting from our network of healthcare professionals - physicians, nurses, radiologists, medical linguists. Each contributor is verified for credentials, specialty, and language proficiency.

04

Supervised Collection

Data collection with real-time quality monitoring. Recording environment validation, acoustic checks, and vocabulary coverage tracking. Every session produces a quality report.

05

De-identification

PHI removal according to HIPAA Safe Harbor and Expert Determination methods. Automated pipeline with manual review for edge cases. Full audit trail documenting every redaction.

06

Secure Delivery

Encrypted transfer to your infrastructure. Complete documentation package: consent records, collection metadata, quality metrics, and compliance certificates. Integration support included.

Regulatory Compliance

The Risk of Non-Compliant Training Data in Healthcare

Healthcare AI operates under overlapping regulatory frameworks. Every dataset we deliver includes documentation for the jurisdictions you operate in.

HIPAA

  • De-identification protocols (Safe Harbor + Expert Determination)
  • Business Associate Agreement available
  • PHI handling procedures with full audit trail

GDPR

  • Voice treated as biometric data per Article 9
  • Explicit individual consent with granular controls
  • Right to erasure supported at individual record level

EU AI Act

  • Healthcare AI classified as high-risk (Annex III)
  • Full data governance documentation (Article 10)
  • Bias testing and representativeness reporting

Institutional Review

  • Experience with IRB/ethics board submissions
  • Participant consent workflows for clinical settings
  • Protocol amendments and ongoing compliance support
Why Specialized

General Crowd Data vs Healthcare-Specialized Collection

The difference between training data that works in a demo and training data that works in a hospital.

Dimension General Crowd Data YPAI Healthcare
Contributors General public, no medical background Physicians, nurses, medical linguists
Vocabulary Scripted medical terms, often mispronounced Natural clinical vocabulary, correct pronunciation
Environment Home recordings, quiet rooms Clinical settings with authentic ambient conditions
Compliance Basic consent, no healthcare certifications HIPAA, GDPR, EU AI Act, IRB-ready
De-identification Not applicable (no real PHI) Safe Harbor + Expert Determination, auditable
Quality Assurance Automated checks only Automated + clinical expert review
Provenance Anonymous crowd workers Verified credentials, documented lineage
Get Started

Discuss Your Clinical Data Needs

Tell us about your healthcare AI project. We will respond with a technical consultation covering data requirements, compliance scope, contributor profiles, and timeline.

Technical consultation within 48 hours
NDA available before detailed discussion
Pilot project option for evaluation

Engineering intake

Inquiry details are treated as confidential. You will receive a response from technical staff.

Include: modality, environment, volume estimate, and any regulatory constraints.

Optional Details

Response from technical staff within 1 business day