J Korean Soc Radiol.  2022 Nov;83(6):1208-1218. 10.3348/jksr.2022.0155.

Understanding and Application of Multi-Task Learning in Medical Artificial Intelligence

• Kim YJ
• Kim KG

• KMID: 2536807
• DOI: http://doi.org/10.3348/jksr.2022.0155

Abstract

In the medical field, artificial intelligence has been used in various ways with many developments. However, most artificial intelligence technologies are developed so that one model can perform only one task, which is a limitation in designing the complex reading process of doctors with artificial intelligence. Multi-task learning is an optimal way to overcome the limitations of single-task learning methods. Multi-task learning can create a model that is efficient and advantageous for generalization by simultaneously integrating various tasks into one model. This study investigated the concepts, types, and similar concepts as multi-task learning, and examined the status and future possibilities of multi-task learning in the medical research.

Keyword

Artificial Intelligence; Machine Learning; Deep Learning; Radiography