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Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support

in Medical Image Computing, iMIMIC 2019, and the 9th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2019, held;

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Medical Content-Based Retrieval for Clinical Decision Support

retrieval of data from visual or multimodal medical databases, disease model-building and clinical decision support systems based on visual or;

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Multimodal Learning for Clinical Decision Support and Clinical Image Based Proce

multimodal data sets for clinical decision support and treatment planning. The CLIP workshops provides a forum for work centered on specific clinical;

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Interpretable and Annotation Efficient Learning for Medical Image Computing

challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer;

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Medical Image Computing and Computer Assisted Intervention - MICCAI 2021

learning; machine learning - interpretability / explainability; and machine learning - uncertainty Part IV: image registration; image-guided;

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Machine Intelligence and Soft Computing

computation, machine learning, metaheuristics and swarm intelligence, neuro-fuzzy system, soft computing and decision support systems, soft computing;

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Advancement of Machine Intelligence in Interactive Medical Image Analysis

in processing, analysing, and utilising all aspects of advanced computational intelligence in medical decision-making based on medical imaging.;

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Advancement of Machine Intelligence in Interactive Medical Image Analysis

in processing, analysing, and utilising all aspects of advanced computational intelligence in medical decision-making based on medical imaging.;

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Recent Studies on Computational Intelligence

, biomedical computing, decision support and decision making. The book is useful for researchers, students, engineers, practitioners and academicians;

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Deep Learning for Medical Decision Support Systems

the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience;

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Deep Learning for Medical Decision Support Systems

the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience;

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Fuzzy Approaches for Soft Computing and Approximate Reasoning: Theories and Applications

machine learning, summarization, interpretability and XAI. Moreover, several application-based papers are included, e.g. on image processing;

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Advanced Machine Vision Paradigms for Medical Image Analysis

. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the;

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Computational Intelligence in Medical Imaging

CI Techniques & Algorithms for a Variety of Medical Imaging SituationsDocuments recent advances and stimulates further research A;

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Computational Intelligence in Medical Imaging

CI Techniques & Algorithms for a Variety of Medical Imaging SituationsDocuments recent advances and stimulates further research A;

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Distributed Computing and Artificial Intelligence, Special Sessions II, 15th International Conference

methods in the areas of Artificial Intelligence and Machine Learning for use in distributed computing as well as decision support systems. As the;

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Congress on Intelligent Systems

, during September 5-6, 2020. It includes novel and innovative work from experts, practitioners, scientists, and decision-makers from academia and;

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Congress on Intelligent Systems

during September 5 - 6, 2020. It includes novel and innovative work from experts, practitioners, scientists and decision-makers from academia and;

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Hardware Accelerator Systems for Artificial Intelligence and Machine Learning

Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti?cial Intelligence and the growth;

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Pattern Recognition and Machine Intelligence

reviewed and selected from 341 submissions. They are organized in topical sections named: Pattern Recognition; Machine Learning; Deep Learning;

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Pattern Recognition and Machine Intelligence

reviewed and selected from 341 submissions. They are organized in topical sections named: Pattern Recognition; Machine Learning; Deep Learning;

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Hybrid Machine Intelligence for Medical Image Analysis

the latest trends in machine learning technologies and computational intelligence for intelligent medical image analysis. The topics covered;

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Context-Aware Machine Learning and Mobile Data Analytics

the broad area of data science and analytics, particularly, with the aim of data-driven intelligent decision making. Thus, we have bestowed a;

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Artificial Intelligence and Machine Learning for EDGE Computing

Artificial Intelligence and Machine Learning for Predictive and Analytical Rendering in Edge Computing focuses on the role of AI and;

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Computational Intelligence and Its Applications

; optimization; planning and scheduling; wireless communication and mobile computing; Internet of Things (IoT) and decision support systems; pattern;

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Image and Signal Processing for Networked eHealth Applications

clinical decision support systems and corresponding medical standards, WWW-based applications, medical collaborative platforms, wireless networking;

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Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches

and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural;

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