Overcoming Computational Resource Limitations in Deep Learning for Healthcare: Strategies Targeting Data, Model, and Computing

Abstract

Deep learning has been identified as an indispensable backbone in health data science. However, the computational constraints faced by many healthcare providers, who may lack access to high-performance computing resources, must be considered. This commentary illustrates three representative strategies from the perspective of data, model, and computing to mitigate computational constraints in resource-limited settings.