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OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging

This book constitutes the refereed proceedings of the Second International Workshop on Context-Aware Surgical Theaters, OR 2.0 2019, and;

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Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology

in both developing new machine learning methods and applications of existing methods to solve challenging problems in clinical neuroimaging;

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Medical Image Computing and Computer Assisted Intervention - MICCAI 2021

learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning;

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Artificial Intelligence and Machine Learning , An Issue of Neuroimaging Clinics of North America

This issue of Neuroimaging Clinics of North America focuses on Artificial Intelligence and Machine Learning and is edited by Dr. Reza;

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Context-Aware Machine Learning and Mobile Data Analytics

context-aware intelligent applications and services. The presented machine learning-based techniques can be employed in a wide range of real-world;

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Machine Learning and Interpretation in Neuroimaging

This book constitutes the revised selected papers from the 4th International Workshop on Machine Learning and Interpretation;

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Context Aware Pervasive Systems and Applications

This textbook explores the current challenges in and future prospects of context-aware pervasive systems and applications. The phenomenal;

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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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Thoughtful Machine Learning

Learn how to apply test-driven development (TDD) to machine-learning algorithms - and catch mistakes that could sink your analysis. In this;

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Microsoft Azure Machine Learning

0;

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Operating Systems Concepts with Java

illustrate many ideas and includes numerous examples that pertain specifically to popular operating systems such as UNIX, Solaris 2, Windows NT and;

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Hardware-Aware Probabilistic Machine Learning Models

learning task, with the overarching goal of balancing the two optimally. The book first motivates extreme-edge computing in the context;

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Machine Learning

Machine Learning is an area of artificial intelligence involving the development of algorithms to discover trends and patterns;

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The Java(tm) Virtual Machine Specification

of applications targeting the Java 2 platform, and is the basis for its security capabilities. This book was written by those directly responsible for the;

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Operating Systems Concepts With Java

to illustrate many ideas and includes numerous examples that pertain specifically to popular operating systems such as UNIX, Solaris 2;

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Machine Learning with Spark -

want to implement various machine-learning concepts in the context of Spark ML, this book is for you. You should be well versed with the Scala and;

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Signal Processing and Machine Learning for Biomedical Big Data

Within the healthcare domain, big data is defined as any ``high volume, high diversity biological, clinical, environmental, and lifestyle;

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Machine Learning for Networking

submissions. They present and discuss new trends in deep and reinforcement learning, pattern recognition and classification for networks, machine;

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Mobile Learning

theoretical understanding of learning in modern mobile-connected societies. Context-aware mobile learning takes advantage of cell phone, mobile, and;

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Mobile Learning

theoretical understanding of learning in modern mobile-connected societies. Context-aware mobile learning takes advantage of cell phone, mobile, and;

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Machine Learning Meets Medical Imaging

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Neuroinflammation in Vascular Dementia

understanding of diseases that lead to cognitive decline. Reviews the clinical aspects and subtypes of dementia Explains;

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Availability, Reliability, and Security in Information Systems

, Reliability and Security in Information Systems, CD-ARES 2016, and the Workshop on Privacy Aware Machine Learning for Health Data Science, PAML 2016;

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Machine Learning for Networking

submissions. They present and discuss new trends in deep and reinforcement learning, patternrecognition and classi cation for networks, machine;

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Efficacy Analysis in Clinical Trials an Update

Machine learning and big data is hot. It is, however, virtually unused in clinical trials. This is so, because randomization is applied to;

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Adult Learning Disorders

clinical practice. One cluster of chapters addresses developmental concerns as children and adolescents with learning disorders approach young;

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Machine Learning for Networking: First International Conference, Mln 2018, Paris, France, November 27-29, 2018, Revised Selected Papers

from 48 submissions. They present new trends in the following topics: Deep and reinforcement learning; Pattern recognition and classification;

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