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020 _a9783030898472
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024 7 _a10.1007/978-3-030-89847-2
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245 1 0 _aMultimodal Learning for Clinical Decision Support
_h[electronic resource] :
_b11th International Workshop, ML-CDS 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings /
_cedited by Tanveer Syeda-Mahmood, Xiang Li, Anant Madabhushi, Hayit Greenspan, Quanzheng Li, Richard Leahy, Bin Dong, Hongzhi Wang.
250 _a1st ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aVIII, 117 p. 47 illus., 43 illus. in color.
_bonline resource.
336 _atext
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337 _acomputer
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338 _aonline resource
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347 _atext file
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490 1 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
_x3004-9954 ;
_v13050
505 0 _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.
520 _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.
650 0 _aImage processing
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650 0 _aComputer vision.
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650 0 _aMachine learning.
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650 0 _aDatabase management.
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650 0 _aSocial sciences
_xData processing.
_983360
650 1 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_931569
650 2 4 _aMachine Learning.
_91831
650 2 4 _aDatabase Management.
_93157
650 2 4 _aComputer Application in Social and Behavioral Sciences.
_931815
700 1 _aSyeda-Mahmood, Tanveer.
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700 1 _aLi, Xiang.
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700 1 _aMadabhushi, Anant.
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700 1 _aGreenspan, Hayit.
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700 1 _aLi, Quanzheng.
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700 1 _aLeahy, Richard.
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700 1 _aDong, Bin.
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700 1 _aWang, Hongzhi.
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776 0 8 _iPrinted edition:
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830 0 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
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856 4 0 _uhttps://doi.org/10.1007/978-3-030-89847-2
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