Jérémie Traoré, Frédéric Balen, Thomas Geeraerts, Sandrine Charpentier, Xavier Dubucs, Charles-Henri Houzé-Cerfon
Is it valid to assess an individual's performance in team training simulation when the supporting team are confederates? A controlled and randomized clinical trial
BMC medical education
lymph node metastasis lnm significant prognostic factor patients head neck cancer ability predict accurately essential treatment optimization pet ct imaging routinely used lnm identification however uncertainties lnm always exist especially small size reactive nodes radiomics deep learning two preferred imagingbased strategies node malignancy prediction radiomics models built based handcrafted features deep learning learn features automatically proposed hybrid predictive model combines manyobjective radiomics moradiomics 3dimensional convolutional neural network 3dcnn evidential reasoning er approach build reliable model proposed new manyobjective radiomics model meanwhile designed 3dcnn fully utilizes spatial contextual information finally outputs fused er approach study predictability two modalities three models built pet ct pet ct results showed model performed best two modalities combined moreover showed quantitative results obtained hybrid model better obtained moradiomics 3dcnn