Healthcare

Generate safe EHR data at scale

Accelerate the development of clinical applications while safeguarding patient privacy.
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Unlock limitless possibilities

Generate safe data
Power LLMs
Boost model robustness

Generate Safe Synthetic Data for Analytics, ML, and Software Development.

  • Clinical Trials

    Synthetic data can help in simulating patient data for clinical trials, facilitating more efficient initial testing phases and protocol development.

  • EHR Analysis

    Enable the safe analysis of electronic health records (EHR) by using synthetic data, maintaining patient privacy while extracting valuable insights for healthcare improvement.

  • Personalized Treatment Plans

    Develop personalized treatment plans using synthetic data that employs differential privacy, ensuring safe and privacy-preserving data analysis.

  • Software Development

    Unlock data access for non-production environments increasing development cycles and productivity while eliminating sensitive data exposure.

Synthesize Training Data for LLMs and Conversational AI

  • Patient Interaction

    Improve patient interaction bots through synthetic data, enhancing automated patient support and communication.

  • Medical Consultation

    Generate synthetic conversations for training AI in understanding diverse medical queries, supporting the development of AI-driven consultation systems.

Boost Model Robustness with Synthetic Data

  • Disease Prediction

    Boost the accuracy and reliability of disease prediction models by integrating synthetic data to cover a wide spectrum of patient conditions and histories.

  • Healthcare Operations

    Improve models that optimize hospital operations and resource allocation by incorporating synthetic data for varied scenarios and patient influxes.

EHR Challenge
Challenge

The data bottleneck

The healthcare industry is in the midst of digital transformation, with advanced data science and AI bringing new possibilities for improving patient care. However, working with EHR poses unique challenges relating to data privacy, data quality, and data availability.
  • Sensitive patient records

    Sensitive patient information is regulated and its use requires adherence to HIPAA, GDPR, and other privacy frameworks.

  • Biased datasets

    EHR records are often imbalanced due to factors like social inequalities in healthcare  and low adverse clinical outcomes.

  • Unavailable clinical records

    Patient data is difficult to find for some medical conditions due to issues in reporting or infrequency of rare diseases.

Solution

Power innovation with synthetic EHR data

Synthetic health data accelerates clinical research while protecting patient privacy by generating artificial records that resemble real EHR without including any actual patient information.

Organizations also use synthetic data to augment AI training datasets by boosting low sample sizes, balancing between classes, filling in missing fields, and  simulating new examples for underrepresented medical conditions.

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Key Benefits

Why synthetic data?

  • Quality EHR records at scale

    Backed by multiple generative AI models and proven across healthcare use cases, scale your data needs as required without compromising on quality or privacy.

  • Mitigate regulatory risks

    With tunable privacy filters and models built with differential privacy—complete with mathematical guarantees, rest assured EHR data is safe.

  • Accelerate better clinical applications

    Make your data asset safe and better so teams can stop worrying about data quality and access and focus on improving patient outcomes.

Healthcare Resources

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