Workshop: Generating Synthetic Data for Healthcare & Life Sciences

Gretel AI's CPO Alex Watson discussed how synthetic data can be used for medical research while maintaining ethical, equitable and fair practices. Synthetic data is an alternative to real-world data generated by computer simulations or algorithms. It has gained popularity in recent years due to advancements in deep learning techniques. Gretel AI uses a language model that trains on sensitive customer data sets while imposing privacy parameters to prevent memorization of data it shouldn't. The resulting artificial data set maintains the same insights and distributions as the original data, but is not based on any real-world person or object. Synthetic data can be used for faster access to medical research data, reducing bias in datasets, generating more samples from limited data sets, and improving overall accuracy of machine learning models.