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Predicting Pathological Complete Response in Rectal Cancer after Chemoradiotherapy with a Random Forest Using 18F-Fluorodeoxyglucose Positron Emission Tomography and Computed Tomography Radiomics.

Annals of Translational Medicine(2020)

Cited 25|Views37
Key words
F-18-fluorodeoxyglucose ([F-18]FDG),positron emission tomography (PET),computed tomography (CT),rectal cancer,radiomics,pathological complete response,random forest (RF),machine learning,artificial intelligence
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