00923nam0-22003131i-450-99000528097040332120070613104418.0000528097FED01000528097(Aleph)000528097FED0100052809719990604d1970----km-y0itay50------baitay---e---00---<<L'>>autorità della BibbiaCharles Harold Doddedizione italiana a cura di Antonio OrnellaBresciaPaideiac1970303 p.21 cmBiblioteca di cultura religiosa21Trad. di A.M. Calao230.041Dodd,Charles-Harold205766Ornella,AntonioITUNINARICAUNIMARCBK990005280970403321230.041 DOD 1ST.REL. 70 s.c.FLFBCFLFBCAutorità della Bibbia268599UNINA04464nam 22007695 450 991050637620332120251010161253.03-030-89847-410.1007/978-3-030-89847-2(CKB)4950000000280216(MiAaPQ)EBC6787291(Au-PeEL)EBL6787291(OCoLC)1281955694(DE-He213)978-3-030-89847-2(BIP)081700810(PPN)258296542(EXLCZ)99495000000028021620211019d2021 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMultimodal Learning for Clinical Decision Support 11th International Workshop, ML-CDS 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings /edited by Tanveer Syeda-Mahmood, Xiang Li, Anant Madabhushi, Hayit Greenspan, Quanzheng Li, Richard Leahy, Bin Dong, Hongzhi Wang1st ed. 2021.Cham :Springer International Publishing :Imprint: Springer,2021.1 online resource (125 pages)Image Processing, Computer Vision, Pattern Recognition, and Graphics,3004-9954 ;130503-030-89846-6 Includes bibliographical references and index.From 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.This 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.Image Processing, Computer Vision, Pattern Recognition, and Graphics,3004-9954 ;13050Image processingDigital techniquesComputer visionMachine learningDatabase managementSocial sciencesData processingComputer Imaging, Vision, Pattern Recognition and GraphicsMachine LearningDatabase ManagementComputer Application in Social and Behavioral SciencesImage processingDigital techniques.Computer vision.Machine learning.Database management.Social sciencesData processing.Computer Imaging, Vision, Pattern Recognition and Graphics.Machine Learning.Database Management.Computer Application in Social and Behavioral Sciences.616.07540285Syeda-Mahmood TanveeredtLi XiangedtMadabhushi AnantedtGreenspan HayitedtLi QuanzhengedtLeahy RichardedtDong BinedtWang HongzhiedtMiAaPQMiAaPQMiAaPQBOOK9910506376203321Multimodal learning for clinical decision support2899375UNINA