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This book is the first overview on Deep Learning (DL) for
biomedical data analysis. It surveys the most recent techniques and
approaches in this field, with both a broad coverage and enough
depth to be of practical use to working professionals. This book
offers enough fundamental and technical information on these
techniques, approaches and the related problems without
overcrowding the reader's head. It presents the results of the
latest investigations in the field of DL for biomedical data
analysis. The techniques and approaches presented in this book deal
with the most important and/or the newest topics encountered in
this field. They combine fundamental theory of Artificial
Intelligence (AI), Machine Learning (ML) and DL with practical
applications in Biology and Medicine. Certainly, the list of topics
covered in this book is not exhaustive but these topics will shed
light on the implications of the presented techniques and
approaches on other topics in biomedical data analysis. The book
finds a balance between theoretical and practical coverage of a
wide range of issues in the field of biomedical data analysis,
thanks to DL. The few published books on DL for biomedical data
analysis either focus on specific topics or lack technical depth.
The chapters presented in this book were selected for quality and
relevance. The book also presents experiments that provide
qualitative and quantitative overviews in the field of biomedical
data analysis. The reader will require some familiarity with AI, ML
and DL and will learn about techniques and approaches that deal
with the most important and/or the newest topics encountered in the
field of DL for biomedical data analysis. He/she will discover both
the fundamentals behind DL techniques and approaches, and their
applications on biomedical data. This book can also serve as a
reference book for graduate courses in Bioinformatics, AI, ML and
DL. The book aims not only at professional researchers and
practitioners but also graduate students, senior undergraduate
students and young researchers. This book will certainly show the
way to new techniques and approaches to make new discoveries.
This book is the first overview on Deep Learning (DL) for
biomedical data analysis. It surveys the most recent techniques and
approaches in this field, with both a broad coverage and enough
depth to be of practical use to working professionals. This book
offers enough fundamental and technical information on these
techniques, approaches and the related problems without
overcrowding the reader's head. It presents the results of the
latest investigations in the field of DL for biomedical data
analysis. The techniques and approaches presented in this book deal
with the most important and/or the newest topics encountered in
this field. They combine fundamental theory of Artificial
Intelligence (AI), Machine Learning (ML) and DL with practical
applications in Biology and Medicine. Certainly, the list of topics
covered in this book is not exhaustive but these topics will shed
light on the implications of the presented techniques and
approaches on other topics in biomedical data analysis. The book
finds a balance between theoretical and practical coverage of a
wide range of issues in the field of biomedical data analysis,
thanks to DL. The few published books on DL for biomedical data
analysis either focus on specific topics or lack technical depth.
The chapters presented in this book were selected for quality and
relevance. The book also presents experiments that provide
qualitative and quantitative overviews in the field of biomedical
data analysis. The reader will require some familiarity with AI, ML
and DL and will learn about techniques and approaches that deal
with the most important and/or the newest topics encountered in the
field of DL for biomedical data analysis. He/she will discover both
the fundamentals behind DL techniques and approaches, and their
applications on biomedical data. This book can also serve as a
reference book for graduate courses in Bioinformatics, AI, ML and
DL. The book aims not only at professional researchers and
practitioners but also graduate students, senior undergraduate
students and young researchers. This book will certainly show the
way to new techniques and approaches to make new discoveries.
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Database and Expert Systems Applications - DEXA 2018 International Workshops, BDMICS, BIOKDD, and TIR, Regensburg, Germany, September 3-6, 2018, Proceedings (Paperback, 1st ed. 2018)
Mourad Elloumi, Michael Granitzer, Abdelkader Hameurlain, Christin Seifert, Benno Stein, …
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R1,567
Discovery Miles 15 670
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Ships in 10 - 15 working days
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This volume constitutes the refereed proceedings of the three
workshops held at the 29th International Conference on Database and
Expert Systems Applications, DEXA 2018, held in Regensburg,
Germany, in September 2018: the Third International Workshop on Big
Data Management in Cloud Systems, BDMICS 2018, the 9th
International Workshop on Biological Knowledge Discovery from Data,
BIOKDD, and the 15th International Workshop on Technologies for
Information Retrieval, TIR. The 25 revised full papers were
carefully reviewed and selected from 33 submissions. The papers
discuss a range of topics including: parallel data management
systems, consistency and privacy cloud computing and graph queries,
web and domain corpora, NLP applications, social media and
personalization
The 14 contributed chapters in this book survey the most recent
developments in high-performance algorithms for NGS data, offering
fundamental insights and technical information specifically on
indexing, compression and storage; error correction; alignment; and
assembly. The book will be of value to researchers, practitioners
and students engaged with bioinformatics, computer science,
mathematics, statistics and life sciences.
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Database and Expert Systems Applications - DEXA 2019 International Workshops BIOKDD, IWCFS, MLKgraphs and TIR, Linz, Austria, August 26-29, 2019, Proceedings (Paperback, 1st ed. 2019)
Gabriele Anderst-Kotsis, A. Min Tjoa, Ismail Khalil, Mourad Elloumi, Atif Mashkoor, …
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R1,557
Discovery Miles 15 570
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Ships in 10 - 15 working days
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This volume constitutes the refereed proceedings of the four
workshops held at the 30th International Conference on Database and
Expert Systems Applications, DEXA 2019, held in Linz, Austria, in
August 2019: The 10th International Workshop on Biological
Knowledge Discovery from Data, BIOKDD 2019, the 3rd International
Workshop on Cyber-Security and Functional Safety in Cyber-Physical
Systems, IWCFS 2019, the 1st International Workshop on Machine
Learning and Knowledge Graphs, MLKgraphs2019, and the 16th
International Workshop on Technologies for Information Retrieval,
TIR 2019. The 26 selected papers discuss a range of topics
including: knowledge discovery, biological data, cyber security,
cyber-physical system, machine learning, knowledge graphs,
information retriever, data base, and artificial intelligent.
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