Machine Learning and Radiomics Applications in Esophageal Cancers Using Non-Invasive Imaging Methods-A Critical Review of Literature.

Cancers (Basel) · 2021 · PMC8158761 · PMID 34069367

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borderline significanceno p-value reported

[ 115 ] validated their radiomics-based model for EC patients receiving nCRT in an independent external cohort, which split risk groups for survival rates with borderline significance.

also in 7,017 other papers

borderline significantno p-value reported

Patients stratified by ML models in different risk groups have a significant or borderline significant difference in survival outcomes.

also in 11,409 other papers

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