Pith. sign in

Citation notice #7636 · 2026-07-11 11:51:01.374780+00:00

Multi-Site Health Research Integrating Complementary Data Sources: A Scoping Review of Statistical Inference Methods for Vertically Partitioned Data

Correction Crossref Open

cites Federated machine learning in healthcare: A systematic review on clinical applications and technical architecture, which carries a correction notice dated 2024-03-21. One-hop deterministic notice: the citation edge exists in the Pith bibliography graph; no model judged whether the citation was load-bearing.

This is not a judgment on the citing paper.

Citing paper Cited paper on Pith Event page Original DOI Notice DOI File a formal challenge All reference changes

01Evidence

Raw extraction · citation context · bibliography index 20

ten Thij, A. Wilbik, Vertical federated learning: a structured literature review, Knowl. Inf. Syst. 67 (2025) 3205-3243. https://doi.org/10.1007/s10115-025- 02356-y. [19] H. Chen, H. Wang, Q. Long, D. Jin, Y . Li, Advancements in Federated Learning: Models, Methods, and Privacy, ACM Comput. Surv. (2024) 3664650. https://doi.org/10.1145/3664650. [20] Z.L. Teo, L. Jin, N. Liu, S. Li, D. Miao, X. Zhang, W.Y . Ng, T.F. Tan, D.M. Lee, K.J. Chua, J. Heng, Y . Liu, R.S.M. Goh, D.S.W. Ting, Federated machine learning in healthcare: A systematic review on clinical applications and technical architecture, Cell Rep. Med. 5 (2024) 101419. https://doi.org/10.1016/j.xcrm.2024.101419. [21] G. Shmueli, To Explain or to Predict?

02Event

Type
Correction
Source
Crossref
Original DOI
10.1016/j.xcrm.2024.101419
Notice DOI
10.1016/j.xcrm.2024.101481
Date
2024-03-21
Title
Federated machine learning in healthcare: A systematic review on clinical applications and technical architecture
Reasons
['Erratum']
Work
Federated machine learning in healthcare: A systematic review on clinical applications and technical architecture (2024) Cell Reports Medicine

Schema constants (for re-runners): correction · crossref

03Dispute this notice

If this citation does not depend on the flagged claim, or the event is wrong, say so. Disputes are public. For a signed challenge against the paper itself, use the formal challenge form.