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

There has been limited exploration of how domain knowledge can be effectively integrated 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.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.trl-1.11
Citations
1
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
2.48
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article

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

Bjoern M. Eskofier, Emmanuelle Salin, Thomas Altstidl, Arijana Bohr
1 citations
Machine Learning in Healthcare
2.48
article

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

Bjoern M. Eskofier, Emmanuelle Salin, Thomas Altstidl, Arijana Bohr
article en
1 citations

Abstract

There has been limited exploration of how domain knowledge can be effectively integrated 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.

Openalex Percentile: Top 9%
Machine Learning in Healthcare
2.48
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