Machine learning-based multiparametric mri radiomics for predicting poor responders after neoadjuvant chemoradiotherapy in rectal cancer patients

HIGHLIGHTS

• who: Jia Wang from the (UNIVERSITY) have published the Article: Machine learning-based multiparametric MRI radiomics for predicting poor responders after neoadjuvant chemoradiotherapy in rectal Cancer patients, in the Journal: (JOURNAL)
• what: The aim of this study was to investigate and validate multiparametric magnetic resonance imaging (MRI)-based machine learning classifiers for early identification of poor responders after neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal (LARC). Although internal validation of this study showed optimal AUCs, data with greater variability are required (different scanners, magnetic_fields, institutions).
• how: The AUCs of the models . . .
  

   

  

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