Data Mining in Biomedical Imaging, Signaling, and Systems

✍ Scribed by Sumeet Dua (ed.), Rajendra Acharya U. (ed.)

• Publisher: Auerbach Publications
• Year: 2011
• Tongue: English
• Leaves: 430
• Category: Library

✦ Synopsis

Data mining can help pinpoint hidden information in medical data and accurately differentiate pathological from normal data. It can help to extract hidden features from patient groups and disease states and can aid in automated decision making. Data Mining in Biomedical Imaging, Signaling, and Systems provides an in-depth examination of the biomedical and clinical applications of data mining. It supplies examples of frequently encountered heterogeneous data modalities and details the applicability of data mining approaches used to address the computational challenges in analyzing complex data.

The book details feature extraction techniques and covers several critical feature descriptors. As machine learning is employed in many diagnostic applications, it covers the fundamentals, evaluation measures, and challenges of supervised and unsupervised learning methods. Both feature extraction and supervised learning are discussed as they apply to seizure-related patterns in epilepsy patients. Other specific disorders are also examined with regard to the value of data mining for refining clinical diagnoses, including depression and recurring migraines. The diagnosis and grading of the world’s fourth most serious health threat, depression, and analysis of acoustic properties that can distinguish depressed speech from normal are also described. Although a migraine is a complex neurological disorder, the text demonstrates how metabonomics can be effectively applied to clinical practice.

The authors review alignment-based clustering approaches, techniques for automatic analysis of biofilm images, and applications of medical text mining, including text classification applied to medical reports. The identification and classification of two life-threatening heart abnormalities, arrhythmia and ischemia, are addressed, and a unique segmentation method for mining a 3-D imaging biomarker, exemplified by evaluation of osteoarthritis, is also presented. Given the widespread deployment of complex biomedical systems, the authors discuss system-engineering principles in a proposal for a design of reliable systems. This comprehensive volume demonstrates the broad scope of uses for data mining and includes detailed strategies and methodologies for analyzing data from biomedical images, signals, and systems.

✦ Table of Contents

Content: 1. Feature extraction methods in biomedical signaling and imaging / Xian Du and Sumeet Dua --
2. Supervised and unsupervised learning methods in biomedical signaling and imaging / Xian Du and Sumeet Dua --
3. Data mining of acoustical properties of speech as indicators of depression / Ananthakrishna T. ... [et al.] --
4. Typicality measure and the creation of predictive models in biomedicine / Mila Kwiatkowska ... [et al.] --
5. Gaussian mixture model-based clustering technique for electrocardiogram analysis / Roshan Joy Martis, Chandan Chakraborty, and Ajoy Kumar Ray --
6. Pattern recognition algorithms for seizure applications / Alan Chiu --
7. Application of parametric and nonparametric methods in arrhythmia classification / Haseena H., K. Paul Joseph, and Abraham T. Mathew --
8. Supervised and unsupervised metabonomic techniques in clinical diagnosis : classification of 677-MTHFR mutations in migraine sufferers / Filippo Molinari ... [et al.] --
9. Automatic grading of adult depression using a backpropagation neural network classifier / Subhagata Chattopadhyay ... [et al.] --
10. Alignment-based clustering of gene expression time-series data / Numanul Subhani ... [et al.] --
11. Mining of imaging biomarkers for quantitative evaluation of osteoarthritis / Xian Du --
12. Supervised classification of digital mammograms / Harpreet Singh and Sumeet Dua --
13. Biofilm image analysis : automatic segmentation methods and applications / Dario Rojas ... [et al.] --
14. Discovering association of diseases in the upper gastrointestinal tract using text mining techniques / S.S. Saraf, G.R. Udupi, and Santosh D. Hajare --
15. Mental health informatics : scopes and challenges / Subhagata Chattopadhyay --
16. Systems engineering for medical informatics / Oliver Faust ... [et al.].
Abstract: "Data mining has rapidly emerged as an enabling, robust, and scalable technique to analyze data for novel patterns, trends, anomalies, structures, and features that can be employed for a variety of biomedical and clinical domains. Approaching the techniques and challenges of image mining from a multidisciplinary perspective, this book presents data mining techniques, methodologies, algorithms, and strategies to analyze biomedical signals and images. Written by experts, the text addresses data mining paradigms for the development of biomedical systems. It also includes special coverage of knowledge discovery in mammograms and emphasizes both the diagnostic and therapeutic fields of eye imaging"--Résumé de l'éditeur