AI in Health: What are the Types of Data Sources on Which a Model Learns?

  • Data is the critical component of developinf solutions using Artificial Intelligence.
  • Data can me divided into 3 types of datasets:
    • a training set which is how the machine learning model learns by tweaking its solution (algorithm)
    • a validation set validation data, assesses the model fit and performance and tunes the model. It which is often a subset of training data.
    • a test set which is a separate dataset and test data that independently assesses the final model fit and performance.
  • Validation is a term that refers both to:
    • the model validation, how well the model performs.
    • clinical validation. How well does this model work in a clinical setting ? Does it impact the outcomes that it is set out to intervene and change? Only if this answer is in the affirmative can it be deployed to the real world.

Note that the presenter has used the concept of Augmented Intelligence instead of Artificial Intelligence. Please refer to the introductory article of this term.

Ivy Lee, MD. Augmented Artificial Intelligence in Dermatology. Core concepts and clinical decision making. 8th World Congress of Teledermatology, Skin Imaging and AI in Skin diseases – November 2020


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