Medical Data Mining and Knowledge Discovery
Medical Data Mining and Knowledge Discovery

Author: Krzysztof J. Cios

Publisher: Physica

Published: 2001-01-12

Total Pages: 528

ISBN-13:

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Modern medicine generates, almost daily, huge amounts of heterogeneous data. For example, medical data may contain SPECT images, signals like ECG, clinical information like temperature, cholesterol levels, etc., as well as the physician's interpretation. Those who deal with such data understand that there is a widening gap between data collection and data comprehension. Computerized techniques are needed to help humans address this problem. This volume is devoted to the relatively young and growing field of medical data mining and knowledge discovery. As more and more medical procedures employ imaging as a preferred diagnostic tool, there is a need to develop methods for efficient mining in databases of images. Other significant features are security and confidentiality concerns. Moreover, the physician's interpretation of images, signals, or other technical data, is written in unstructured English which is very difficult to mine. This book addresses all these specific features.

Interactive Knowledge Discovery and Data Mining in Biomedical Informatics
Interactive Knowledge Discovery and Data Mining in Biomedical Informatics

Author: Andreas Holzinger

Publisher: Springer

Published: 2014-06-17

Total Pages: 373

ISBN-13: 3662439689

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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 and Knowledge Discovery for Engineering Systems Health Management
Machine Learning and Knowledge Discovery for Engineering Systems Health Management

Author: Ashok N. Srivastava

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 489

ISBN-13: 1439841799

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This volume presents state-of-the-art tools and techniques for automatically detecting, diagnosing, and predicting the effects of adverse events in an engineered system. It emphasizes the importance of these techniques in managing the intricate interactions within and between engineering systems to maintain a high degree of reliability. Reflecting the interdisciplinary nature of the field, the book explains how the fundamental algorithms and methods of both physics-based and data-driven approaches effectively address systems health management in application areas such as data centers, aircraft, and software systems.

Information Discovery on Electronic Health Records
Information Discovery on Electronic Health Records

Author: Vagelis Hristidis

Publisher: CRC Press

Published: 2009-12-10

Total Pages: 334

ISBN-13: 1420090410

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Exploiting the rich information found in electronic health records (EHRs) can facilitate better medical research and improve the quality of medical practice. Until now, a trivial amount of research has been published on the challenges of leveraging this information. Addressing these challenges, Information Discovery on Electronic Health Records exp

Healthcare Data Analytics
Healthcare Data Analytics

Author: Chandan K. Reddy

Publisher: CRC Press

Published: 2015-06-23

Total Pages: 756

ISBN-13: 148223212X

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At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available

Temporal Data Mining
Temporal Data Mining

Author: Theophano Mitsa

Publisher: CRC Press

Published: 2010-03-10

Total Pages: 398

ISBN-13: 1420089773

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From basic data mining concepts to state-of-the-art advances, this book covers the theory of the subject as well as its application in a variety of fields. It discusses the incorporation of temporality in databases as well as temporal data representation, similarity computation, data classification, clustering, pattern discovery, and prediction. The book also explores the use of temporal data mining in medicine and biomedical informatics, business and industrial applications, web usage mining, and spatiotemporal data mining. Along with various state-of-the-art algorithms, each chapter includes detailed references and short descriptions of relevant algorithms and techniques described in other references.

Data Mining Methods for Knowledge Discovery
Data Mining Methods for Knowledge Discovery

Author: Krzysztof J. Cios

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 508

ISBN-13: 1461555892

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Data Mining Methods for Knowledge Discovery provides an introduction to the data mining methods that are frequently used in the process of knowledge discovery. This book first elaborates on the fundamentals of each of the data mining methods: rough sets, Bayesian analysis, fuzzy sets, genetic algorithms, machine learning, neural networks, and preprocessing techniques. The book then goes on to thoroughly discuss these methods in the setting of the overall process of knowledge discovery. Numerous illustrative examples and experimental findings are also included. Each chapter comes with an extensive bibliography. Data Mining Methods for Knowledge Discovery is intended for senior undergraduate and graduate students, as well as a broad audience of professionals in computer and information sciences, medical informatics, and business information systems.

Advances in Knowledge Discovery and Data Mining
Advances in Knowledge Discovery and Data Mining

Author: Usama M. Fayyad

Publisher:

Published: 1996

Total Pages: 638

ISBN-13:

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Eight sections of this book span fundamental issues of knowledge discovery, classification and clustering, trend and deviation analysis, dependency derivation, integrated discovery systems, augumented database systems and application case studies. The appendices provide a list of terms used in the literature of the field of data mining and knowledge discovery in databases, and a list of online resources for the KDD researcher.

Introduction to Computational Health Informatics
Introduction to Computational Health Informatics

Author: Arvind Kumar Bansal

Publisher: CRC Press

Published: 2020-01-08

Total Pages: 784

ISBN-13: 1000761592

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This class-tested textbook is designed for a semester-long graduate or senior undergraduate course on Computational Health Informatics. The focus of the book is on computational techniques that are widely used in health data analysis and health informatics and it integrates computer science and clinical perspectives. This book prepares computer science students for careers in computational health informatics and medical data analysis. Features Integrates computer science and clinical perspectives Describes various statistical and artificial intelligence techniques, including machine learning techniques such as clustering of temporal data, regression analysis, neural networks, HMM, decision trees, SVM, and data mining, all of which are techniques used widely used in health-data analysis Describes computational techniques such as multidimensional and multimedia data representation and retrieval, ontology, patient-data deidentification, temporal data analysis, heterogeneous databases, medical image analysis and transmission, biosignal analysis, pervasive healthcare, automated text-analysis, health-vocabulary knowledgebases and medical information-exchange Includes bioinformatics and pharmacokinetics techniques and their applications to vaccine and drug development

Data Mining
Data Mining

Author: Krzysztof J. Cios

Publisher: Springer Science & Business Media

Published: 2007-10-05

Total Pages: 601

ISBN-13: 0387367950

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This comprehensive textbook on data mining details the unique steps of the knowledge discovery process that prescribes the sequence in which data mining projects should be performed, from problem and data understanding through data preprocessing to deployment of the results. This knowledge discovery approach is what distinguishes Data Mining from other texts in this area. The book provides a suite of exercises and includes links to instructional presentations. Furthermore, it contains appendices of relevant mathematical material.