Aditya Mahadevan, Ronald Rivera, Mahan Najhawan, Soheil Saadat, Matthew Strehlow, G V Ramana Rao, Julie Youm
Assessing the Efficacy of a Novel Massive Open Online Soft Skills Course for South Asian Healthcare Professionals
Journal of medical systems
determining lymphoma subtypes crucial step better patient treatment targeting potentially increase survival chances context existing gold standard diagnosis method relies gene expression technology highly expensive timeconsuming making less accessibility although alternative diagnosis methods based ihc immunohistochemistry technologies exist recommended still suffer similar limitations less accurate whole slide image wsi analysis using deep learning models shown promising potential cancer diagnosis could offer costeffective faster alternatives existing methods work propose vision transformerbased framework distinguishing dlbcl diffuse large bcell lymphoma cancer subtypes highresolution wsis end introduce multimodal architecture train classifier model various wsi modalities leverage model knowledge distillation process efficiently guide learning monomodal classifier experimental study conducted lymphoma dataset 157 patients shows promising performance monomodal classification model outperforming six recent stateoftheart methods addition powerlaw curve estimated experimental data suggests training data reasonable number additional patients model could achieve competitive diagnosis accuracy ihc technologies furthermore efficiency framework confirmed additional experimental study external breast cancer dataset bci dataset