ResearcherNational Taiwan UniversityActive in the last 2 years

Danni Wu

ORCID-verified (high confidence, 0.95), identity_conf@1As of 8 November 2026

Matched on ORCID iD 0000-0003-3834-8937; OpenAlex author ID A5064669865. Sources: OpenAlex.

Their work

Papers: 2
Trials: 0
Grants: 0
Labs led: 0
Collaborators: 3

Papers, trials and grants by year

2026: 2 papers

Papers 2

PanMETAI - a high performance tabular foundation model for accurate pancreatic cancer diagnosis via NMR metabolomics. Co-author DOI 10.1038/s41467-026-69426-9 ↗
Author Correction: PanMETAI - a high performance tabular foundation model for accurate pancreatic cancer diagnosis via NMR metabolomics. Co-author DOI 10.1038/s41467-026-72208-y ↗

Closest collaborators

The 3 strongest of 3 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.

Yu‐Ting Chang · 2 shared papers, 2026 · strength 0.50
- Paper PanMETAI - a high performance tabular foundation model for accurate pancreatic cancer diagnosis via NMR metabolomics. DOI 10.1038/s41467-026-69426-9 ↗
- Paper Author Correction: PanMETAI - a high performance tabular foundation model for accurate pancreatic cancer diagnosis via … DOI 10.1038/s41467-026-72208-y ↗
Ming‐Chu Chang · 2 shared papers, 2026 · strength 0.50
- Paper PanMETAI - a high performance tabular foundation model for accurate pancreatic cancer diagnosis via NMR metabolomics. DOI 10.1038/s41467-026-69426-9 ↗
- Paper Author Correction: PanMETAI - a high performance tabular foundation model for accurate pancreatic cancer diagnosis via … DOI 10.1038/s41467-026-72208-y ↗
Chun-Mei Hu · 2 shared papers, 2026 · strength 0.50
- Paper PanMETAI - a high performance tabular foundation model for accurate pancreatic cancer diagnosis via NMR metabolomics. DOI 10.1038/s41467-026-69426-9 ↗
- Paper Author Correction: PanMETAI - a high performance tabular foundation model for accurate pancreatic cancer diagnosis via … DOI 10.1038/s41467-026-72208-y ↗

How to reach this person

A chain of introductions through people who have published, run trials or held grants together (warm_path@1: fewest links first, then the strongest). Built from public records only; no contact details are kept.