digitalhumanOS™ Data: 12.3M PAC/LTC Patients
The strength of [digitalhumanOS™](/platform) lies in the vast amount of data it has been trained on. With a dataset encompassing 12.
Key Facts
- digitalhumanOS is trained on a large dataset of PAC/LTC patients.
- The data includes diverse demographics and clinical conditions.
- The data is used to improve the accuracy and reliability of AI algorithms.
The strength of digitalhumanOS™ lies in the vast amount of data it has been trained on. With a dataset encompassing 12.3 million patients in post-acute care (PAC) and long-term care (LTC) settings, digitalhumanOS has a deep understanding of the unique challenges and complexities of this population. This extensive dataset includes diverse demographics, clinical conditions, and care settings, ensuring that digitalhumanOS is accurate and reliable. This large dataset allows for more accurate and nuanced assessments.
Size and Scope of the Dataset
digitalhumanOS is trained on data from 12.3 million PAC/LTC patients.
Diversity of Patient Demographics
The dataset includes diverse demographics, ensuring that digitalhumanOS is applicable to a wide range of patients.
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Variety of Clinical Conditions
The dataset includes a variety of clinical conditions, allowing digitalhumanOS to identify and address a wide range of health issues.
Data Quality and Validation
The data is rigorously validated to ensure accuracy and reliability.
Conclusion
The 12.3 million PAC/LTC patient dataset is a cornerstone of digitalhumanOS. This large and diverse dataset ensures that digitalhumanOS is accurate, reliable, and applicable to a wide range of patients. By leveraging this data, digitalhumanOS can provide valuable insights and improve patient care in PAC and LTC settings. The size of the dataset is a key differentiator. Explore GIA®'s clinical validation across 12.3M patient records.
Sources & References
- Translating AI Research into Reality: Summary of the 2025 Voice AI Symposium. Frontiers in Digital Health. DOI: 10.3389/fdgth.2026.1754426. Vanderbilt, MIT, Mayo Clinic, NIH Bridge2AI.
- Mapping the Neurophysiological Link Between Voice and Autonomic Function: A Scoping Review. 2025. Biology (MDPI). DOI: 10.3390/biology14101382.
- Scienza Health internal validation: 12.3M patients, 27B clinical events, 2,500+ speech biomarkers.
David Kaiser is the Founder and CEO of Scienza Health. He leads the development of GIA® and digitalhumanOS™, a clinically validated speech biomarker platform that screens for 46 cognitive and neurological conditions in under 5 minutes.
This content is intended for informational purposes and does not constitute medical advice. Editorially reviewed by David Kaiser, CEO of Scienza Health, for accuracy in post-acute care operations.
Frequently Asked Questions
How many patients are included in the digitalhumanOS dataset?
The dataset includes data from 12.3 million PAC/LTC patients.
What types of data are included in the dataset?
The dataset includes demographics, clinical conditions, and care settings.
How is the data used to improve digitalhumanOS?
The data is used to train and refine AI algorithms, improving accuracy and reliability.
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