License High-quality
Healthcare/Medical Data
for AI & ML Models

Off-the-shelf Healthcare/Medical Datasets to jumpstart your Healthcare AI project

Medical And Healthcare Datasets

Plug-in the medical data you’ve been missing today

Medical and Healthcare datasets for Machine Learning

Physician Dictation Audio Data

Our de-identified dataset for healthcare include 31 different specialties audio files dictated by physicians describing patients’ clinical condition and plan of care based on physician-patient encounters in the hospital/clinical setting.

Off-the-Shelf Physician Dictation Audio Files:

  • 257,977 hours of Real-world Physician Dictation Speech Dataset from 31 specialties’ to train Healthcare Speech models
  • Dictation audio captured from various devices like Telephone Dictation (54.3%), Digital Recorder (24.9%), Speech Mic (5.4%), Smart Phone (2.7%) and Unknown (12.7%)
  • PII Redacted Audio & Transcripts adhering to Safe Harbor Guidelines in conformance with HIPAA

Transcribed Medical Records

Transcribed medical records refers to transcription of physician and patient conversation, transcription of medical reports and medical assessment. It helps in mapping the medical history of the patient for future visits and also acts as a refence point for the doctors. It helps the doctor to evaluate the present condition of the patient and suggest a suitable treatment.

Off-the-Shelf Transcribed Medical Records:

  • Transcription of 257,977 hours of Real-world Physician Dictation from 31 specialties to train Healthcare Speech models
  • Transcribed Medical Records from various work types like Operative Report, Discharge Summary, Consultation Note, Admit Note, ED Note, Clinic Note, Radiology Report, etc.
  • PII Redacted Audio & Transcripts adhering to Safe Harbor Guidelines in conformance with HIPAA
Transcribed Medical Records

Electronic Health Records (EHR)

Electronic Health Records or EHR are medical records that contains patient’s medical history, diagnoses, prescription, treatment plans, vaccination or immunization dates, allergies, radiology images (CT Scan, MRI, X-Rays), and laboratory tests & more.

Off-the-Shelf Electronic Health Records (EHR):

  • 5.1M+ Records and physician audio files in 31 specialties
  • Real-world gold-standard medical records to train Clinical NLP and other Document AI models
  • Metadata information like MRN (Anonymized), Admission Date, Discharge Date, Length of Stay days, Gender, Patient Class, Payer, Financial Class, State, Discharge Disposition, Age, DRG, DRG Description, $ Reimbursement, AMLOS, GMLOS, Risk of mortality, Severity of illness, Grouper, Hospital Zip Code, etc.
  • Medical Records from various US states and region- North East (46%), South (9%), Midwest (3%), West (28%), Others (14%)
  • Medical Records belonging to all Patient Classes covered- Inpatient, Outpatient (Clinical, Rehab, Recurring, Surgical Day Care), Emergency.
  • Medical Records belonging to all Patient Age Groups <10 yrs (7.9%), 11-20 yrs (5.7%), 21-30 yrs (10.9%), 31-40 yrs (11.7%), 41-50 yrs (10.4%), 51-60 yrs (13.8%), 61-70 yrs (16.1%), 71-80 yrs (13.3%), 81-90 yrs (7.8%), 90+ yrs (2.4%)
  • Patient Gender ratio of 46% (Male) and 54% (Female)
  • PII Redacted Documents adhering to Safe Harbor Guidelines in conformance with HIPAA
Electronic Health Records (Ehr)
  • Medical Records belonging to all Patient Age Groups <10 yrs (7.9%), 11-20 yrs (5.7%), 21-30 yrs (10.9%), 31-40 yrs (11.7%), 41-50 yrs (10.4%), 51-60 yrs (13.8%), 61-70 yrs (16.1%), 71-80 yrs (13.3%), 81-90 yrs (7.8%), 90+ yrs (2.4%)
  • Patient Gender ratio of 46% (Male) and 54% (Female)
  • PII Redacted Documents adhering to Safe Harbor Guidelines in conformance with HIPAA
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