Reply to: "Reevaluating feature selection in machine learning-based radiomics for hepatocellular carcinoma: Bridging the gap between predictive accuracy and biological relevance".
사설/논평
0/5 보강
APA
Vithayathil M, Koku D, et al. (2025). Reply to: "Reevaluating feature selection in machine learning-based radiomics for hepatocellular carcinoma: Bridging the gap between predictive accuracy and biological relevance".. Journal of hepatology, 83(4), e210-e211. https://doi.org/10.1016/j.jhep.2025.07.005
MLA
Vithayathil M, et al.. "Reply to: "Reevaluating feature selection in machine learning-based radiomics for hepatocellular carcinoma: Bridging the gap between predictive accuracy and biological relevance".." Journal of hepatology, vol. 83, no. 4, 2025, pp. e210-e211.
PMID
40659063 ↗
같은 제1저자의 인용 많은 논문 (2)
- The use of advanced machine learning to predict outcomes after atezolizumab plus bevacizumab for advanced hepatocellular carcinoma: a retrospective cohort study.
- Machine learning based radiomic models outperform clinical biomarkers in predicting outcomes after immunotherapy for hepatocellular carcinoma.