SHAP can be employed to interpret machine learning models used in various nanotechnology applications. For instance, in drug delivery systems, SHAP values can help elucidate how different features like particle size, surface charge, and hydrophobicity impact the efficiency of the delivery system. Similarly, in nanomaterials design, SHAP can help identify which factors most significantly influence material properties like strength, conductivity, and reactivity.
