Back to search

Article

Established Machine Learning Matches Tabular Foundation Models in Clinical Predictions

2026-02-04

Abstract excerpt

Foundation models (FMs) promise to standardise predictive modeling across domains, yet their clinical value for tabular data remains unproven. To test this, we performed a large, fully reproducible benchmark of TabPFN, a leading FM for tabular prediction, against twelve established machine learning (ML) methods across twelve binary clinical tasks. Cohorts spanned 788 - 139,528 patients across diverse outcomes, inc...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
1e4af4cd-99cf-5da3-a674-39cf0f6e58b6
DOI
10.64898/2026.02.02.26345274
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Established Machine Learning Matches Tabular Foundation Models in Clinical PredictionsDOI 10.64898/2026.02.02.26345274
Select a neighboring publication to make it the new centre.