Figure 9.

The development and application of an MSI-based machine learning model for burn wound classification. Horizontal arm: Steps used to build an accurate training database or library for the algorithm. Initially, a sample of the tissue classes is selected and sorted into their appropriate class using expert-guided criteria. Images of these tissues are gathered and used to populate a tissue reference training database. From these data, machine learning algorithms assign quantitative thresholds to the tissue classes of interest. Vertical arm: Once the classification algorithm is complete, the technique generates classified outputs in seconds to minutes of patients in the clinical setting. To see this illustration in color, the reader is referred to the web version of this article at www.liebertpub.com/wound