Expression of Concern: De Bari et al. Could 18-FDG PET-CT Radiomic Features Predict the Locoregional Progression-Free Survival in Inoperable or Unresectable Oesophageal Cancer? Cancers 2022, 14, 4043
Abstract
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
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Taxonomy
TopicsRadiomics and Machine Learning in Medical Imaging · Esophageal Cancer Research and Treatment · Lung Cancer Diagnosis and Treatment
In this notice, the Cancers Editorial Office alerts readers to concerns related to this article [1]. Following publication, concerns were raised to the Editorial Office regarding the Institutional Review Board approval in this study. The Editor-in-Chief has decided to issue this expression of concern while an investigation is being conducted. The authors’ institution has been contacted to contribute to this investigation.
Once this process has been completed, the Editorial Office will provide an update on this situation and announce any post-publication modification deemed to be necessary, as per MDPI’s Update to Published Papers policy.
The reference list from the paper itself. Each links out to its DOI / PubMed record.
- 1De Bari B. Lefevre L. Henriques J. Gatta R. Falcoz A. Mathieu P. Borg C. Dinapoli N. Boulahdour H. Boldrini L. Could 18-FDG PET-CT Radiomic Features Predict the Locoregional Progression-Free Survival in Inoperable or Unresectable Oesophageal Cancer?Cancers 202214404310.3390/cancers 1416404336011035 PMC 9406583 · doi ↗ · pubmed ↗