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020 _a9783030609467
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024 7 _a10.1007/978-3-030-60946-7
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050 4 _aQ334-342
050 4 _aTA347.A78
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245 1 0 _aMultimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures
_h[electronic resource] :
_b10th International Workshop, ML-CDS 2020, and 9th International Workshop, CLIP 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4-8, 2020, Proceedings /
_cedited by Tanveer Syeda-Mahmood, Klaus Drechsler, Hayit Greenspan, Anant Madabhushi, Alexandros Karargyris, Marius George Linguraru, Cristina Oyarzun Laura, Raj Shekhar, Stefan Wesarg, Miguel Ángel González Ballester, Marius Erdt.
250 _a1st ed. 2020.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2020.
300 _aXII, 138 p. 4 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
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 ;
_v12445
505 0 _aCLIP 2020 -- Optimal Targeting Visualizations for Surgical Navigation of Iliosacral Screws -- Prediction of Type II Diabetes Onset with Computed Tomography and Electronic Medical Records -- A Radiomics-based Machine Learning Approach to Assess Collateral Circulation in Stroke on Non-contrast Computed Tomography -- Image-based Subthalamic Nucleus Segmentation for Deep Brain Surgery With Electrophysiology Aided Refinement -- 3D Slicer Craniomaxillofacial Modules Support Patient-specific Decision-making for Personalized Healthcare in Dental Research -- Learning Representations of Endoscopic Videos to Detect Tool Presence Without Supervision -- Single-shot Deep Volumetric Regression for Mobile Medical Augmented Reality -- A Baseline Approach for AutoImplant: the MICCAI 2020 Cranial Implant Design Challenge -- Adversarial Prediction of Radiotherapy Treatment Machine Parameters -- ML-CDS 2020 -- Soft Tissue Sarcoma Co-Segmentation in Combined MRI and PET/CT Data -- Towards Automated Diagnosis with Attentive Multi-Modal Learning Using Electronic Health Records and Chest X-rays -- LUCAS: LUng CAncer Screening with Multimodal Biomarkers -- Automatic Breast Lesion Classification by Joint Neural Analysis of Mammography and Ultrasound.
520 _aThis book constitutes the refereed joint proceedings of the 10th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2020, and the 9th International Workshop on Clinical Image-Based Procedures, CLIP 2020, held in conjunction with the 23rd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic. The 4 full papers presented at ML-CDS 2020 and the 9 full papers presented at CLIP 2020 were carefully reviewed and selected from numerous submissions to ML-CDS and 10 submissions to CLIP. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. The CLIP workshops provides a forum for work centered on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.
650 0 _aArtificial intelligence.
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650 0 _aComputer vision.
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650 0 _aSocial sciences
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650 0 _aBioinformatics.
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650 0 _aDatabase management.
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650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputer Vision.
_9171796
650 2 4 _aComputer Application in Social and Behavioral Sciences.
_931815
650 2 4 _aComputational and Systems Biology.
_931619
650 2 4 _aDatabase Management.
_93157
700 1 _aSyeda-Mahmood, Tanveer.
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700 1 _aDrechsler, Klaus.
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700 1 _aGreenspan, Hayit.
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700 1 _aMadabhushi, Anant.
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700 1 _aKarargyris, Alexandros.
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700 1 _aLinguraru, Marius George.
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700 1 _aOyarzun Laura, Cristina.
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700 1 _aShekhar, Raj.
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700 1 _aWesarg, Stefan.
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700 1 _aGonzález Ballester, Miguel Ángel.
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700 1 _aErdt, Marius.
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830 0 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
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