Interpreting County Level COVID-19 Infection and Feature Sensitivity using Deep Learning Time Series Models. (arXiv:2210.03258v1 [cs.LG])

Interpretable machine learning plays a key role in healthcare because it is
challenging in understanding feature importance in deep learning model
predictions. We propose a novel framework that uses deep learning to study
feature sensitivity for model predictions. This work combines sensitivity
analysis with heterogeneous time-series deep learning model prediction, which
corresponds to the interpretations of spatio-temporal features. We forecast
county-level COVID-19 infection using the Temporal Fusion Transformer. We then
use the sensitivity analysis extending Morris Method to see how …

arxiv county covid covid-19 deep learning feature series time series