Citation notice #9500 · 2026-08-11 00:18:03.520017+00:00
An Integrated Optimization and Deep Learning Pipeline for Predicting Live Birth Success in IVF Using Feature Optimization and Transformer-Based Models
Correction
Crossref
Open
cites 10.1007/s10815-022-02562-5, which carries a correction notice dated 2022-08-31. One-hop deterministic notice: the citation edge exists in the Pith bibliography graph; no model judged whether the citation was load-bearing.
Citing paper Event page Original DOI Notice DOI File a formal challenge All reference changes
01Evidence
Raw extraction · bibliography line · bibliography index 7
Ueno, S., Berntsen, J., Ito, M., Okimura, T., & Kato, K. (2022). Correlation between an annotation- free embryo scoring system based on deep learning and live birth/neonatal outcomes after single vitrified-warmed blastocyst transfer: a single -centre, large-cohort retrospective study. Journal of assisted reproduction and genetics, 39(9), 2089–2099. DOI:10.1007/s10815-022-02562-5
02Event
- Type
- Correction
- Source
- Crossref
- Original DOI
- 10.1007/s10815-022-02562-5
- Notice DOI
- 10.1007/s10815-022-02605-x
- Date
- 2022-08-31
- Title
- Correction to: Correlation between an annotation-free embryo scoring system based on deep learning and live birth/neonatal outcomes after single vitrified-warmed blastocyst transfer: a single-centre, large-cohort retrospective study
- Reasons
- ['Correction']
- Work
- - (2022) Journal of Assisted Reproduction and Genetics
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.