A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data

Understand

Multi-task learning (MTL) is a machine learning technique aiming to improve model performance by leveraging information across many tasks.

• It has been used extensively on various data modalities, including electronic health record (EHR) data.
• However, despite significant use on EHR data, there has been little systematic investigation of the utility of MTL across the diverse set of possible tasks and training schemes of interest in healthcare.
• In this work, we examine MTL across a battery of tasks on EHR time-series data.