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Synthetic Data Generation

Train your own machine learning models before obtaining real patient data with data synthesized to simulate patients with rheumatic disease

Generate Data
Number of Samples

Determines the number of fictitious patient samples to generate.

The condition for the fictitious patient samples to emulate.

Determines the percentage of null values to include in the generated fictitious patient data (Serum or Demographic), adding difficulty to illness identification. Enter a decimal.

Data to Include

Specifies data types for feature generation. Serum data is continuous; all other features are binary. Check all that apply.

Show Y-true values as

Determines the y-true values to generate. Choose either all 1s or all 0s to indicate whether the samples should be used for training. This can be combined with other target disease data with a different y-true for comprehensive training.

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