Perspective: Leveraging Domain Knowledge for Tabular Machine Learning in the Medical Domain

Arijana Bohr, Thomas Altstidl, Bjoern Eskofier, Emmanuelle Salin

Keywords: Medical Machine Learning, Tabular Machine Learning, Domain Knowledge, Informed Machine Learning

TL;DR: This paper presents an overview of methods for integrating domain knowledge into medical tabular machine learning

Abstract:

There has been limited exploration of how to effectively integrate domain knowledge into machine learning for medical tabular data.
Traditional approaches often rely on non-generalizable processes tailored to specific datasets.
In contrast, recent advances in deep learning for language and tabular data are leading the way toward more generalizable and scalable methods of domain knowledge inclusion.
In this paper, we first explore the need for domain knowledge in medical tabular data, categorize types of medical domain knowledge, and discuss how each can be leveraged in tabular machine learning.
We then outline strategies for integrating this knowledge at various stages of the machine learning pipeline. Finally, building on recent advances in tabular deep learning, we propose future research directions to support the integration of domain knowledge.

Submission Number: 16