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Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study
Research article (Cancer Imaging, 2023) · cited 18× · AI/ML
Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study
Summary
Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study is a scholarly article[1].
Key Facts
Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study. Retrieved May 24, 2026, from https://4ort.xyz/entity/interpretability-of-radiomics-models-is-improved-when-using-feature-group-selection-strategies-for-predicting-molecular-
MLA“Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/interpretability-of-radiomics-models-is-improved-when-using-feature-group-selection-strategies-for-predicting-molecular-.
BibTeX@misc{4ortxyz_interpretability-of-radiomics-models-is-improved-when-using-feature-group-selection-strategies-for-predicting-molecular-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study}}, year = {2026}, url = {https://4ort.xyz/entity/interpretability-of-radiomics-models-is-improved-when-using-feature-group-selection-strategies-for-predicting-molecular-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study — https://4ort.xyz/entity/interpretability-of-radiomics-models-is-improved-when-using-feature-group-selection-strategies-for-predicting-molecular- (retrieved 2026-05-24)