Interactive Knowledge Discovery and Data Mining in Biomedical Informatics : State-of-the-Art and Future Challenges / edited by Andreas Holzinger, Igor Jurisica.

Format:

Book

Contributor:

Holzinger, Andreas, Editor.

Jurisica, Igor, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Information systems and applications, incl. Internet/Web, and HCI ; SL 3, 8401

Information Systems and Applications, incl. Internet/Web, and HCI ; 8401

Language:

English

Subjects (All):

Data mining.

Information storage and retrieval systems.

Medical informatics.

Data Mining and Knowledge Discovery.

Information Storage and Retrieval.

Health Informatics.

Local Subjects:

Data Mining and Knowledge Discovery.

Information Storage and Retrieval.

Health Informatics.

Physical Description:

1 online resource (XX, 357 pages) : 56 illustrations

Edition:

1st ed. 2014.

Contained In:

Springer Nature eBook

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014.

System Details:

text file PDF

Summary:

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 toward precision medicine has resulted in an explosion in the amount of biomedical data sets generated. Despite the fact that human experts are very good at pattern recognition in three dimensions or less, most of the data are 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 the methodologies and approaches of two fields offer ideal conditions for unraveling these problems: human-computer interaction (HCI) and knowledge discovery/data mining (KDD), with the goal of supporting human capabilities with machine learning. This 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: (1) data integration, data pre-processing, and data mapping; (2) data mining algorithms; (3) graph-based data mining; (4) entropy-based data mining; (5) topological data mining; (6) visualization; (7) privacy, data protection, safety, and security. .

Contents:

Knowledge Discovery and Data Mining in Biomedical Informatics: The Future Is in Integrative, Interactive Machine Learning Solutions

Visual Data Mining: Effective Exploration of the Biological Universe

Darwin or Lamarck? Future Challenges in Evolutionary Algorithms for Knowledge Discovery and Data Mining

On the Generation of Point Cloud Data Sets: Step One in the Knowledge Discovery Process

Adapted Features and Instance Selection for Improving Co-training

Knowledge Discovery and Visualization of Clusters for Erythromycin Related Adverse Events in the FDA Drug Adverse Event Reporting System

On Computationally-Enhanced Visual Analysis of Heterogeneous Data and Its Application in Biomedical Informatics

A Policy-Based Cleansing and Integration Framework for Labour and Healthcare Data

Interactive Data Exploration Using Pattern Mining

Resources for Studying Statistical Analysis of Biomedical Data and R

A Kernel-Based Framework for Medical Big-Data Analytics

On Entropy-Based Data Mining

Sparse Inverse Covariance Estimation for Graph Representation of Feature Structure

Multi-touch Graph-Based Interaction for Knowledge Discovery on Mobile Devices: State-of-the-Art and Future Challenges

Intelligent Integrative Knowledge Bases: Bridging Genomics, Integrative Biology and Translational Medicine

Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges

Protecting Anonymity in Data-Driven Biomedical Science

Biobanks - A Source of Large Biological Data Sets: Open Problems and Future Challenges

On Topological Data Mining.

Other Format:

Printed edition:

ISBN:

978-3-662-43968-5

9783662439685

Access Restriction:

Restricted for use by site license.