Transfer learning is a machine learning technique where a model developed for a particular task is reused as the starting point for a model on a second task. It leverages the knowledge gained from one domain to improve performance in another domain that has limited data. In the context of epidemiology, transfer learning can be particularly useful due to the challenges of obtaining large and high-quality datasets.
