Validate Model: Testing and Monitoring

Testing and monitoring /pre-deployment enables clinician, product manager, marketing executive to validate AI algorithms independently. Pre-deployment / Validation project is a merger of three essential components of any AI validation project i.e. Data, AI Inference, Ground Truth.
  • Data (Dataset) refers to the actual image data, either CT, MR, CR, DX, MG, US etc, on which an AI algorithm is to be tested.
  • AI inference refers to output created by AI algorithms when run on a specific dataset.
  • GT refers to the ‘actual’ labels for each of the cases / images in the dataset.
Once a Pre-deployment project is created by merging the three components - i.e. data, AI output and GT - there are multiple different validation techniques / pipelines that can be used to evaluate the performance of the AI, and share feedback with the developers of the AI.