Expression of Concern: A practical approach for colorectal cancer diagnosis based on machine learning
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
TopicsCOVID-19 diagnosis using AI · AI in cancer detection · Explainable Artificial Intelligence (XAI)
After this article [1] was published, the following concerns were noted:
The corresponding author acknowledged the citation issues and provided alternatives for the two retracted references; however, the Editors determined that the replacements did not adequately support the cited statements.
The corresponding author stated that the data cannot be provided due to patient confidentiality and institutional regulations. The Editors consider this to be sufficient to meet the requirements of the data policy related to sensitive patient data.
The Data Availability statement is updated to: Requests for data access may be directed to the Head of the Information Technology Department of Thai Nguyen National Hospital via [email protected].
In light of the unresolved reference issues, the PLOS One Editors issue this Expression of Concern.
The reference list from the paper itself. Each links out to its DOI / PubMed record.