What is it about?

Using AI in medicine has the potential to greatly improve healthcare outcomes, but it is important that physicians are involved to ensure the accuracy, explainability, and generalizability of the technology. One way to do this is by creating a hybrid model that combines AI with medical knowledge. This means that doctors and other medical professionals would work alongside AI technology, using their expertise to train the algorithms and interpret the results. In this paper, we discuss how integrating medical knowledge into AI technologies can provide a framework for overcoming one of the most important drawbacks of machine learning in applications, the curse of dimensionality.

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Why is it important?

Hybrid modeling in medicine is important because it helps us leverage the benefits of AI in medicine while ensuring that the technology is developed and used responsibly, accurately, and effectively to improve healthcare outcomes.


This research demonstrates how a collaboration between medical professionals and AI can enhance healthcare. By creating a hybrid model that integrates medical knowledge with AI technology, the accuracy and reliability of the predictions can be improved while reducing the amount of data required.

Moein E. Samadi
Joint Research Center for Computational Biomedicine

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This page is a summary of: A training strategy for hybrid models to break the curse of dimensionality, PLoS ONE, September 2022, PLOS, DOI: 10.1371/journal.pone.0274569.
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