LEADER 04465nam 22007695 450 001 996464439703316 005 20230810174204.0 010 $a3-030-89847-4 024 7 $a10.1007/978-3-030-89847-2 035 $a(CKB)4950000000280216 035 $a(MiAaPQ)EBC6787291 035 $a(Au-PeEL)EBL6787291 035 $a(OCoLC)1281955694 035 $a(DE-He213)978-3-030-89847-2 035 $a(BIP)081700810 035 $a(PPN)258296542 035 $a(EXLCZ)994950000000280216 100 $a20211019d2021 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMultimodal Learning for Clinical Decision Support$b[electronic resource] $e11th International Workshop, ML-CDS 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings /$fedited by Tanveer Syeda-Mahmood, Xiang Li, Anant Madabhushi, Hayit Greenspan, Quanzheng Li, Richard Leahy, Bin Dong, Hongzhi Wang 205 $a1st ed. 2021. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021. 215 $a1 online resource (125 pages) 225 1 $aImage Processing, Computer Vision, Pattern Recognition, and Graphics ;$v13050 311 $a3-030-89846-6 320 $aIncludes bibliographical references and index. 327 $aFrom Picoscale Pathology to Decascale Disease: Image Registration with a Scattering Transform and Varifolds for Manipulating Multiscale Data -- Multi-Scale Hybrid Transformer Networks: Application to Prostate Disease Classification -- Predicting Treatment Response in Prostate Cancer Patients Based on Multimodal PET/CT for Clinical Decision Support -- A Federated Multigraph Integration Approach for Connectional Brain Template Learning -- SAMA: Spatially-Aware Multimodal Network with Attention for Early Lung Cancer Diagnosis -- Fully Automatic Head and Neck Cancer Prognosis Prediction in PET/CT -- Feature Selection for Privileged Modalities in Disease Classification -- Merging and Annotating Teeth and Roots from Automated Segmentation of Multimodal Images -- Structure and Feature based Graph U-Net for Early Alzheimer's Disease Prediction -- A Method for Predicting Alzheimer's Disease based on the Fusion of Single Nucleotide Polymorphisms and Magnetic Resonance Feature Extraction. 330 $aThis book constitutes the refereed joint proceedings of the 11th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2021, held in conjunction with the 24th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2021, in Strasbourg, France, in October 2021. The workshop was held virtually due to the COVID-19 pandemic. The 10 full papers presented at ML-CDS 2021 were carefully reviewed and selected from numerous submissions. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. 410 0$aImage Processing, Computer Vision, Pattern Recognition, and Graphics ;$v13050 606 $aImage processing$xDigital techniques 606 $aComputer vision 606 $aMachine learning 606 $aDatabase management 606 $aSocial sciences$xData processing 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aMachine Learning 606 $aDatabase Management 606 $aComputer Application in Social and Behavioral Sciences 615 0$aImage processing$xDigital techniques. 615 0$aComputer vision. 615 0$aMachine learning. 615 0$aDatabase management. 615 0$aSocial sciences$xData processing. 615 14$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aMachine Learning. 615 24$aDatabase Management. 615 24$aComputer Application in Social and Behavioral Sciences. 676 $a616.07540285 702 $aSyeda-Mahmood$b Tanveer$4edt 702 $aLi$b Xiang$4edt 702 $aMadabhushi$b Anant$4edt 702 $aGreenspan$b Hayit$4edt 702 $aLi$b Quanzheng$4edt 702 $aLeahy$b Richard$4edt 702 $aDong$b Bin$4edt 702 $aWang$b Hongzhi$4edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996464439703316 996 $aMultimodal learning for clinical decision support$92899375 997 $aUNISA