Abstract

In Our Ever More Complex World, the Field of Analytics Has Dramatically Increased its Importance. Gut Feeling is No Longer Sufficient in Decision Making, But Intuition Has to Be Combined with Support from the Huge Amount of Data Available Today. Even If the Amount of Data is Enormous, the Quality of the Data is Not Always Good. Problems Arise in at Least Two Situations: I) the Data is Imprecise by Nature and Ii) the Data is Incomplete (Or There Are Missing Parts in the Data Set). Both Situations Are Problematic and Need to Be Addressed Appropriately. If These Problems Are Solved, Applications Are to Be Found in Various Interesting Fields. We Aim at Achieving Significant Methodology Development as Well as Creative Solutions in the Domain of Medicine, Information Systems and Risk Management. This Paper Sets Focus Especially on Missing Data Problems in the Field of Medicine When Presenting a New Project in its Very First Phase.

Department(s)

Engineering Management and Systems Engineering

Keywords and Phrases

Big Data; Health care; Huntington's disease; Machine Learning; Missing values

International Standard Book Number (ISBN)

978-145034337-4

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Association for Computing Machinery, All rights reserved.

Publication Date

29 Jun 2016

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