Physician Dictation Audio Datasets for Healthcare AI
Access 257,977 Hours of Medical Audio Data Across 31 Specialties
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Physician Dictation Audio Datasets for Machine Learning
Our de-identified dataset for healthcare includes 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 Medical Audio Dataset from 31 specialties’ to train Healthcare ASR 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
Medical Audio Data by Gender
| Speciality | Patient Audio Files (Playtime in Hours) | Total No. of Audio Files |
|---|---|---|
Total | 257,977 | 5,172,766 |
| Male | 58,850 | 2,444,910 |
| Female | 113,406 | 1,290,900 |
| Unknown | 85,721 | 1,436,956 |
Medical Audio Data by Specialty
| Speciality | Patient Audio Files (Playtime in Hours) | Total No. of Audio Files |
|---|---|---|
| Pain Medicine | 1 | 11 |
| Podiatric Surgery | 4 | 24 |
| Plastic surgery – specialty | 13 | 183 |
| Physician Asst. | 6 | 38 |
| Physical Therapist | 114 | 1713 |
| Physical Medicine & Rehabilitation | 1347 | 23523 |
| Pediatrics | 877 | 9271 |
| Pediatric surgery | 2 | 23 |
| Pediatric specialty | 35 | 682 |
| Pediatric pulmonology | 4 | 40 |
| Pediatric Dentistry | 15 | 420 |
| Pathology | 1143 | 43462 |
| PANP | 10760 | 145960 |
| Podiatry | 892 | 12056 |
| Pain Management | 2 | 30 |
| Otolaryngology | 995 | 19548 |
| Osteopathic | 310 | 5566 |
| Orthopedic | 4849 | 145053 |
| Orthopaedics & Sports Medicine | 149 | 3165 |
| Oral surgery | 1 | 13 |
| Oral & Maxillofacial Surgeon | 1 | 8 |
| Ophthalmology | 609 | 19299 |
| OPERATIVE CARE | 0 | 5 |
| Oncology | 6816 | 82300 |
| Occupational Therapist | 8 | 68 |
| Surgery | 14431 | 236788 |
| Wound Care | 15 | 211 |
| Vascular/General | 9 | 268 |
| VASCULAR SURGERY | 19 | 156 |
| Urology | 3170 | 96934 |
| Upper gastrointestinal surgery | 4 | 58 |
| Unknown | 42269 | 748054 |
| Trauma & orthopedics | 140 | 1308 |
| Transplant | 3 | 32 |
| Thoracic surgery | 4 | 37 |
| Thoracic medicine | 5 | 27 |
| Surgical specialty | 22 | 290 |
| Surgery Physician Assistant | 0 | 3 |
| Occupational medicine | 79 | 763 |
| Sports Medicine | 3 | 49 |
| Speech Therapy | 29 | 327 |
| Rheumatology | 13 | 124 |
| Resident | 46 | 641 |
| Rehabilitation | 2515 | 30078 |
| Radiology | 10962 | 630983 |
| Pulmonary | 3809 | 64368 |
| Psychotherapy (specialty) | 50 | 229 |
| Psychiatry | 8871 | 70269 |
| PRIMARY CARE ATTENDING | 1 | 7 |
| Preventive Medicine | 21 | 191 |
| Dental | 55 | 1233 |
| General | 26 | 313 |
| Gastroenterology | 3127 | 62158 |
| Family Practice | 262 | 2498 |
| Family Nurse Practitioner | 424 | 9018 |
| Family Medicine | 13639 | 263480 |
| Endocrinology | 219 | 3212 |
| Emergency Room Specialist | 30 | 378 |
| Emergency | 3675 | 62256 |
| ED Physician Assistant | 0 | 70 |
| Ear, Nose And Throat | 51 | 658 |
| Diagnostic Radiology | 255 | 7591 |
| Dermatology | 148 | 3474 |
| General dental practice | 2 | 25 |
| Critical Care | 707 | 9645 |
| Clinical physiology | 50 | 160 |
| Clinical hematology | 0 | 2 |
| Cardiothoracic surgery | 1 | 10 |
| Cardiothoracic | 17 | 122 |
| Cardiology | 67504 | 1566721 |
| APRN | 163 | 1693 |
| Anesthetics | 1 | 9 |
| Anesthesiology | 677 | 22280 |
| Allergy and Immunology | 1152 | 22202 |
| Accident & emergency | 9 | 359 |
| IH-Industrial Health | 73 | 945 |
| OB/GYN | 2424 | 42739 |
| Nurse Practitioner – Family | 9 | 113 |
| Nurse Practitioner | 81 | 432 |
| Neurosurgery | 86 | 755 |
| Neurology | 1476 | 17786 |
| Neuro/TBI | 173 | 1157 |
| Nephrology | 2431 | 39821 |
| Medicine | 5 | 122 |
| Medical oncology | 16 | 67 |
| Internal Medicine, Pulmonary Medicine, Critical Care Medicine And Sleep Medicine | 5 | 102 |
| Internal Medicine And Nephrology | 15 | 111 |
| Internal Medicine | 42604 | 623072 |
Total | 257,977 | 5,172,766 |
| Hospitalist | 99 | 1493 |
| Hospice & Palliative Medicine | 4 | 41 |
| HIM | 0 | 19 |
| Hematology – Oncology | 22 | 394 |
| Gynecology | 4 | 25 |
| GI | 55 | 550 |
| Geriatric Medicine | 461 | 5323 |
| General surgery | 237 | 2220 |
| General Surgeon | 27 | 893 |
| General Psychiatry | 3 | 36 |
| General medicine | 30 | 327 |
Medical Audio Data by Device
| Speciality | Patient Audio Files (Playtime in Hours) | Total No. of Audio Files |
|---|---|---|
Total | 257,977 | 5,172,766 |
| IPHONE | 666 | 32,382 |
| Digital Recorder | 1,659 | 22,377 |
| Mixed type | 69,818 | 1,408,679 |
| SmartPhone | 51,533 | 1,306,405 |
| SpeechMic | 10,329 | 257,730 |
| Telephone Dictation | 120,867 | 2,071,557 |
| Unknown | 3,104 | 73,636 |
We deal with all types of Data Licensing i.e., text, audio, video, or image. The datasets consist of Medical datasets for ML: Physician Dictation Dataset, Physician Clinical Notes, Medical Conversation Dataset, Medical Transcription Dataset, Doctor-Patient Conversation, Medical Text Data, Medical Images – CT Scan, MRI, Ultra Sound (collected basis custom requirements).
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Frequently Asked Questions (FAQ)
1. What is physician dictation audio data?
Physician dictation audio data consists of audio files where doctors describe a patient’s clinical condition, treatment plan, or medical history during consultations or hospital visits.
2. Why is physician dictation audio data important for AI/ML projects?
This data is crucial for training AI models in speech recognition, natural language processing (NLP), and clinical documentation automation. It helps build systems for transcribing, analyzing, and improving healthcare documentation workflows.
3. What types of medical audio datasets are available?
The dataset includes 257,977 hours of real-world physician dictation from 31 medical specialties. Audio is recorded using various devices, including telephones, digital recorders, smartphones, and speech microphones.
4. Is the medical audio data de-identified?
Yes, all audio files are de-identified to remove Personally Identifiable Information (PII), ensuring patient confidentiality.
5. Does the dataset comply with HIPAA and other regulations?
Yes, the datasets adhere to HIPAA and Safe Harbor Guidelines, along with other global privacy standards.
6. Can the datasets be customized?
Yes, datasets can be tailored to specific specialties, demographics, or recording device types based on project requirements.
7. Are these datasets scalable for large projects?
Absolutely. The datasets are extensive, with millions of audio files, making them suitable for both small-scale and large-scale AI/ML projects.
8. How does the data integrate into AI models?
The medical audio data and corresponding transcripts are provided in standard formats that can be seamlessly integrated into speech recognition and natural language processing (NLP) models.
9. How is data quality ensured?
The audio data undergoes rigorous quality checks, and domain experts validate annotations to ensure accuracy and reliability.
10. Are the datasets scalable for large AI projects?
The cost depends on factors such as the volume of data, customization, and project scope. We request that you fill out the “Contact Us” form with your requirements to receive the best quote.
11. What are the delivery timelines for these datasets?
Delivery timelines vary based on the size and complexity of the project, but are structured to meet deadlines efficiently.
12. How can physician dictation audio datasets improve healthcare AI?
These datasets enhance AI capabilities in automating clinical documentation, improving transcription accuracy, and enabling better decision-making for healthcare providers.