Response to "On patient-level splitting, contrast-free claims and unsupported comparators in Machine learning-based classification of multiple sclerosis lesion activity using multi-sequence MRI radiomics".
- DOI
- 10.5114/pjr/219935
- Published
- 2026
- Container
- Polish journal of radiology
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.5114/pjr/219935,
title = {Response to "On patient-level splitting, contrast-free claims and unsupported comparators in Machine learning-based classification of multiple sclerosis lesion activity using multi-sequence MRI radiomics".},
author = {Elhaie M and Shahbazi-Gahrouei D},
year = {2026},
journal = {Polish journal of radiology},
doi = {10.5114/pjr/219935},
url = {https://doi.org/10.5114/pjr/219935}
}RIS
TY - JOUR TI - Response to "On patient-level splitting, contrast-free claims and unsupported comparators in Machine learning-based classification of multiple sclerosis lesion activity using multi-sequence MRI radiomics". AU - Elhaie M AU - Shahbazi-Gahrouei D PY - 2026 JO - Polish journal of radiology DO - 10.5114/pjr/219935 UR - https://doi.org/10.5114/pjr/219935 ER -
APA
M, E., & D, S. (2026). Response to "On patient-level splitting, contrast-free claims and unsupported comparators in Machine learning-based classification of multiple sclerosis lesion activity using multi-sequence MRI radiomics".. Polish journal of radiology. https://doi.org/10.5114/pjr/219935
Source records
- pubmed · retrieved 2026-09-25T09:06:47.386Z