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|a 9783030609467
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|a Syeda-Mahmood, Tanveer
|e [editor]
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|a Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures
|h Elektronische Ressource
|b 10th International Workshop, ML-CDS 2020, and 9th International Workshop, CLIP 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings
|c edited 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
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|a 1st ed. 2020
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|a Cham
|b Springer International Publishing
|c 2020, 2020
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|a XII, 138 p. 4 illus
|b online resource
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|a CLIP 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
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|a Bioinformatics
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|a Computational and Systems Biology
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|a Computer vision
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|a Computer Application in Social and Behavioral Sciences
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|a Artificial Intelligence
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|a Social sciences / Data processing
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|a Computer Vision
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|a Database Management
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|a Artificial intelligence
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|a Database management
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|a Drechsler, Klaus
|e [editor]
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|a Greenspan, Hayit
|e [editor]
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|a Madabhushi, Anant
|e [editor]
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|a eng
|2 ISO 639-2
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|b Springer
|a Springer eBooks 2005-
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|a Image Processing, Computer Vision, Pattern Recognition, and Graphics
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|a 10.1007/978-3-030-60946-7
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|u https://doi.org/10.1007/978-3-030-60946-7?nosfx=y
|x Verlag
|3 Volltext
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|a 006.3
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|a This 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
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