Facing complex models, both computer simulation and machine learning practitioners have pursued similar objectives: to see how results could be broken down and linked to the inputs. Whether it is called Sensitivity Analysis or Variable Importance in the context of explainable AI, some of their methods share an important component: the Shapley values.

Let’s dig deeper on the important factors of the French Covid-19 patient orientation algorithm! The short answer is fever, diarrhea and number of risk factors, but the real answer is that your target population matters a lot.
Follow me on this journey with 3 variable importance methods and get some insights about how factors interact.

Were you aware that there is an official French decision tree to orient patients towards relevant medical services, depending on their Covid-19 related symptoms? I transformed it into a point-based scoring system (100% logically equivalent), so that a patient can compute his/her score by adding simple weights. Using these Covid-19 orientation algorithms, a more general comparative analysis is carried out concerning decision trees and scoring systems.