Interactive Knowledge Discovery And Data Mining In Biomedical Informatics
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Interactive Knowledge Discovery And Data Mining In Biomedical Informatics
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Author : Andreas Holzinger
language : en
Publisher: Springer
Release Date : 2014-06-17
Interactive Knowledge Discovery And Data Mining In Biomedical Informatics written by Andreas Holzinger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-17 with Computers categories.
One of the grand challenges in our digital world are the large, complex and often weakly structured data sets, and massive amounts of unstructured information. This “big data” challenge is most evident in biomedical informatics: the trend towards precision medicine has resulted in an explosion in the amount of generated biomedical data sets. Despite the fact that human experts are very good at pattern recognition in dimensions of = 3; most of the data is high-dimensional, which makes manual analysis often impossible and neither the medical doctor nor the biomedical researcher can memorize all these facts. A synergistic combination of methodologies and approaches of two fields offer ideal conditions towards unraveling these problems: Human–Computer Interaction (HCI) and Knowledge Discovery/Data Mining (KDD), with the goal of supporting human capabilities with machine learning./ppThis state-of-the-art survey is an output of the HCI-KDD expert network and features 19 carefully selected and reviewed papers related to seven hot and promising research areas: Area 1: Data Integration, Data Pre-processing and Data Mapping; Area 2: Data Mining Algorithms; Area 3: Graph-based Data Mining; Area 4: Entropy-Based Data Mining; Area 5: Topological Data Mining; Area 6 Data Visualization and Area 7: Privacy, Data Protection, Safety and Security.
Machine Learning For Health Informatics
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Author : Andreas Holzinger
language : en
Publisher: Springer
Release Date : 2016-12-09
Machine Learning For Health Informatics written by Andreas Holzinger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-09 with Computers categories.
Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds, it is aimed to support human intelligence with machine intelligence. This state-of-the-art survey is an output of the international HCI-KDD expert network and features 22 carefully selected and peer-reviewed chapters on hot topics in machine learning for health informatics; they discuss open problems and future challenges in order to stimulate further research and international progress in this field.
Advanced Data Analytics In Health
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Author : Philippe J. Giabbanelli
language : en
Publisher: Springer
Release Date : 2018-04-20
Advanced Data Analytics In Health written by Philippe J. Giabbanelli and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-20 with Technology & Engineering categories.
This book introduces readers to the methods, types of data, and scale of analysis used in the context of health. The challenges of working with big data are explored throughout the book, while the benefits are also emphasized through the discoveries made possible by linking large datasets. Methods include thorough case studies from statistics, as well as the newest facets of data analytics: data visualization, modeling and simulation, and machine learning. The diversity of datasets is illustrated through chapters on networked data, image processing, and text, in addition to typical structured numerical datasets. While the methods, types of data, and scale have been individually covered elsewhere, by bringing them all together under one “umbrella” the book highlights synergies, while also helping scholars fluidly switch between tools as needed. New challenges and emerging frontiers are also discussed, helping scholars grasp how methods will need to change in response to the latest challenges in health.
Information Technology In Bio And Medical Informatics
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Author : M. Elena Renda
language : en
Publisher: Springer
Release Date : 2016-08-05
Information Technology In Bio And Medical Informatics written by M. Elena Renda and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-05 with Computers categories.
This book constitutes the refereed proceedings of the 7th International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2016, held in Porto, Portugal, in September 2016, in conjunction with DEXA 2016. The 9 revised long papers presented together with 11 poster papers were carefully reviewed and selected from 26 submissions. The papers address the following topics: biomedical data analysis and warehousing; information technologies in brain science; and social networks and process analysis in biomedicine.
Machine Learning And Knowledge Extraction
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Author : Andreas Holzinger
language : en
Publisher: Springer
Release Date : 2017-08-23
Machine Learning And Knowledge Extraction written by Andreas Holzinger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-23 with Computers categories.
This book constitutes the refereed proceedings of the IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2017, held in Reggio, Italy, in August/September 2017. The 24 revised full papers presented were carefully reviewed and selected for inclusion in this volume. The papers deal with fundamental questions and theoretical aspects and cover a wide range of topics in the field of machine learning and knowledge extraction. They are organized in the following topical sections: MAKE topology; MAKE smart factory; MAKE privacy; MAKE VIS; MAKE AAL; and MAKE semantics.
Information Technology In Bio And Medical Informatics
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Author : Miroslav Bursa
language : en
Publisher: Springer
Release Date : 2014-08-19
Information Technology In Bio And Medical Informatics written by Miroslav Bursa and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-19 with Computers categories.
This book constitutes the refereed proceedings of the 5th International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2014, held in Munich, Germany, in September 2014, in conjunction with DEXA 2014. The 9 revised long papers presented together with 3 short papers were carefully reviewed and selected from numerous submissions. The papers address the following topics: clustering and bioinformatics; medical image and data processing; and knowledge discovery and machine learning in medicine.
Hybrid Intelligent Systems
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Author : Ajith Abraham
language : en
Publisher: Springer Nature
Release Date : 2021-04-16
Hybrid Intelligent Systems written by Ajith Abraham and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-16 with Technology & Engineering categories.
This book highlights the recent research on hybrid intelligent systems and their various practical applications. It presents 58 selected papers from the 20th International Conference on Hybrid Intelligent Systems (HIS 2020) and 20 papers from the 12th World Congress on Nature and Biologically Inspired Computing (NaBIC 2020), which was held online, from December 14 to 16, 2020. A premier conference in the field of artificial intelligence, HIS - NaBIC 2020 brought together researchers, engineers and practitioners whose work involves intelligent systems, network security and their applications in industry. Including contributions by authors from 25 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of science and engineering.
Human Computer Interaction And Knowledge Discovery In Complex Unstructured Big Data
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Author : Andreas Holzinger
language : en
Publisher: Springer
Release Date : 2013-06-26
Human Computer Interaction And Knowledge Discovery In Complex Unstructured Big Data written by Andreas Holzinger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-26 with Computers categories.
This book constitutes the refereed proceedings of the Third Workshop on Human-Computer Interaction and Knowledge Discovery, HCI-KDD 2013, held in Maribor, Slovenia, in July 2013, at SouthCHI 2013. The 20 revised papers presented were carefully reviewed and selected from 68 submissions. The papers are organized in topical sections on human-computer interaction and knowledge discovery, knowledge discovery and smart homes, smart learning environments, and visualization data analytics.
Solving Large Scale Learning Tasks Challenges And Algorithms
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Author : Stefan Michaelis
language : en
Publisher: Springer
Release Date : 2016-07-02
Solving Large Scale Learning Tasks Challenges And Algorithms written by Stefan Michaelis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-02 with Computers categories.
In celebration of Prof. Morik's 60th birthday, this Festschrift covers research areas that Prof. Morik worked in and presents various researchers with whom she collaborated. The 23 refereed articles in this Festschrift volume provide challenges and solutions from theoreticians and practitioners on data preprocessing, modeling, learning, and evaluation. Topics include data-mining and machine-learning algorithms, feature selection and feature generation, optimization as well as efficiency of energy and communication.
Machine Learning And Knowledge Discovery In Databases
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Author : Frank Hutter
language : en
Publisher: Springer Nature
Release Date : 2021-02-24
Machine Learning And Knowledge Discovery In Databases written by Frank Hutter and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-24 with Computers categories.
The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic. The 232 full papers and 10 demo papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. The volumes are organized in topical sections as follows: Part I: Pattern Mining; clustering; privacy and fairness; (social) network analysis and computational social science; dimensionality reduction and autoencoders; domain adaptation; sketching, sampling, and binary projections; graphical models and causality; (spatio-) temporal data and recurrent neural networks; collaborative filtering and matrix completion. Part II: deep learning optimization and theory; active learning; adversarial learning; federated learning; Kernel methods and online learning; partial label learning; reinforcement learning; transfer and multi-task learning; Bayesian optimization and few-shot learning. Part III: Combinatorial optimization; large-scale optimization and differential privacy; boosting and ensemble methods; Bayesian methods; architecture of neural networks; graph neural networks; Gaussian processes; computer vision and image processing; natural language processing; bioinformatics. Part IV: applied data science: recommendation; applied data science: anomaly detection; applied data science: Web mining; applied data science: transportation; applied data science: activity recognition; applied data science: hardware and manufacturing; applied data science: spatiotemporal data. Part V: applied data science: social good; applied data science: healthcare; applied data science: e-commerce and finance; applied data science: computational social science; applied data science: sports; demo track.