Different Synthetic Data In Health Care-Techniques Of Building Synthetic Data For Clinical Trial
Synthetic data is key for accelerating deep learning. Clinical Trial applications have a wide data distribution, and datasets from the real world may not fully encompass. Some of the underlying probabilities for risk evaluation during the new drug development process may not be available by using only real-world datasets.
Types Of Synthetic Data
The first step to generating synthetic data is to understand what type of synthetic data you need. There are three categories of synthetic data, and each of these will give you something unique. These include:
1. Fully Synthetic Data
This type of synthetic data does not derive from any original dataset. That means that all the variables are completely available, and the reidentification of a unit is next to impossible.
2. Partially Synthetic Data
Keep in mind that it mostly replaced sensitive data with synthetic data where the privacy of patients or other people is at stake. Such synthetic data heavily depends on the imputation model. Of course, that leads to a reduced model dependence.
However, that does not mean that some disclosure is possible that owes to the true value that remains…
