Critical inconsistencies in the quality of electronic healthcare and medical records (EHR/EMR) pose significant challenges to healthcare researchers and practitioners. Quality gaps in EHR and EMR are caused by many factors including social inequalities in healthcare access, low rates of adverse clinical outcomes, or the general unavailability of patient records.
In this on-demand webinar, Gretel Product Manager, Nicole Pang, and Principal Machine Learning Engineer, Kendrick Boyd, explore the role of synthetic data in improving AI accuracy and reducing bias in healthcare datasets.
In this on-demand webinar, you can expect to:
- Explore where innovation in AI-powered tools in the healthcare industry is headed
- Gain valuable insights into how generative AI techniques like conditional data generation create high-quality synthetic healthcare records in minutes
- Dive into some real world examples of EHR & EMR synthesis
