Corrigendum to ‘Machine learning for prediction of 30-day mortality in patients with advanced cancer: comparing pan-cancer and single-cancer models’ [ESMO Real World Data and Digital Oncology 8 (2025), 100146]

The authors regret: the DOI link provided for the supplementary material in the article directs readers to a different article throughout the article (DOI: https://doi.org/10.1016/j.esmogo.2025.100172). The correct DOI, directing to the correct study would instead be https://doi.org/10.1016/j.esmorw.2025.100146.

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Publication Details

Journal
ESMO Real World Data and Digital Oncology
Published
2026-06-30
DOI
https://doi.org/10.1016/j.esmorw.2026.100747
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

Corrigendum to ‘Machine learning for prediction of 30-day mortality in patients with advanced cancer: comparing pan-cancer and single-cancer models’ [ESMO Real World Data and Digital Oncology 8 (2025), 100146]

S. Bjerregaard-Michelsen, M. Bøgsted, L.Ø. Poulsen, A. Bjerrum et al.
ESMO Real World Data and Digital Oncology
Radiomics and Machine Learning in Medical Imaging
article

Corrigendum to ‘Machine learning for prediction of 30-day mortality in patients with advanced cancer: comparing pan-cancer and single-cancer models’ [ESMO Real World Data and Digital Oncology 8 (2025), 100146]

S. Bjerregaard-Michelsen, M. Bøgsted, L.Ø. Poulsen, A. Bjerrum, C. Vesteghem
article en

Abstract

The authors regret: the DOI link provided for the supplementary material in the article directs readers to a different article throughout the article (DOI: https://doi.org/10.1016/j.esmogo.2025.100172). The correct DOI, directing to the correct study would instead be https://doi.org/10.1016/j.esmorw.2025.100146.

ESMO Real World Data and Digital OncologyVol. 13
Aalborg University Hospital (DK), Copenhagen University Hospital (DK), Rigshospitalet (DK)
Openalex Percentile: Top 7%
Radiomics and Machine Learning in Medical Imaging
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