Interpretability of machine learning based prediction models in healthcare

Understand

There is a need of ensuring machine learning models that are interpretable.

• Higher interpretability of the model means easier comprehension and explanation of future predictions for end-users.
• Further, interpretable machine learning models allow healthcare experts to make reasonable and data-driven decisions to provide personalized decisions that can ultimately lead to higher quality of service in healthcare.
• Generally, we can classify interpretability approaches in two groups where the first focuses on personalized interpretation (local interpretability) while the second summarizes prediction models on a population level (global interpretability).