國立虎尾科技大學 |

Intelligent data analysis for biomedical applications = challenges and solutions /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Intelligent data analysis for biomedical applications/ edited by Jude Hemanth, Deepak Gupta, Valentina Emilia Balas.
Reminder of title:	challenges and solutions /
other author:	Hemanth, D. Jude,
Published:	London :Academic Press, : 2019.,
Description:	1 online resource.
Subject:	Bioinformatics. -
Online resource:	https://www.sciencedirect.com/science/book/9780128155530
ISBN:	9780128156438 (electronic bk.)

Intelligent data analysis for biomedical applications = challenges and solutions /
Intelligent data analysis for biomedical applicationschallenges and solutions /[electronic resource] :edited by Jude Hemanth, Deepak Gupta, Valentina Emilia Balas. - London :Academic Press,2019. - 1 online resource. - Intelligent data centric systems. - Intelligent data centric systems..

Includes bibliographical references and index.

Front Cover; Intelligent Data Analysis for Biomedical Applications; Copyright Page; Contents; List of Contributors; 1 IoT-Based Intelligent Capsule Endoscopy System: A Technical Review; 1.1 Introduction; 1.2 Data Acquisition; 1.2.1 Image Sensor; 1.2.2 Optical Sensor; 1.2.3 Pressure, Temperature, and pH-Monitoring Sensor; 1.2.4 Other Ingestible Sensors; 1.3 On-Chip Data-Processing Unit; 1.3.1 Image Compression; 1.3.2 Application Specific Integrated Circuit Design; 1.3.3 Radiofrequency Transmission; 1.3.4 Power Management; 1.4 Data Management of Wireless Capsule Endoscopy Systems

Intelligent Data Analysis for Biomedical Applications: Challenges and Solutions presents specialized statistical, pattern recognition, machine learning, data abstraction and visualization tools for the analysis of data and discoveryof mechanisms that create data. It provides computational methods and tools for intelligent data analysis, with an emphasis on problem-solving relating to automated data collection, such as computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and more. This book provides useful references for educational institutions, industry professionals, researchers, scientists, engineers and practitioners interested in intelligent data analysis, knowledge discovery, and decision support in databases.

ISBN: 9780128156438 (electronic bk.)Subjects--Topical Terms:

583857
Bioinformatics.
Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: QH324.2

Dewey Class. No.: 005.7

Intelligent data analysis for biomedical applications = challenges and solutions /
LDR:04796cam a2200325 a 4500 001 1043018
006 m o d
007 cr cnu---unuuu
008 211216s2019 enka gob 001 0 eng d
020 $a 9780128156438 (electronic bk.)
020 $a 0128156430 (electronic bk.)
020 $a 9780128155530
020 $a 0128155531
035 $a (OCoLC)1090301530
035 $a on1090301530
040 $a N$T $b eng $c N$T $d N$T $d OPELS $d EBLCP $d UKMGB $d YDX $d UKAHL $d OCLCF $d OCLCQ $d UMI $d OCLCQ $d S2H $d OCLCO $d ERF $d OCLCO $d LVT $d OCLCA
041 0 $a eng
050 4 $a QH324.2
082 0 4 $a 005.7 $2 23
245 0 0 $a Intelligent data analysis for biomedical applications $h [electronic resource] : $b challenges and solutions / $c edited by Jude Hemanth, Deepak Gupta, Valentina Emilia Balas.
260 $a London : $b Academic Press, $c 2019.
300 $a 1 online resource.
490 1 $a Intelligent data centric systems
504 $a Includes bibliographical references and index.
505 0 $a Front Cover; Intelligent Data Analysis for Biomedical Applications; Copyright Page; Contents; List of Contributors; 1 IoT-Based Intelligent Capsule Endoscopy System: A Technical Review; 1.1 Introduction; 1.2 Data Acquisition; 1.2.1 Image Sensor; 1.2.2 Optical Sensor; 1.2.3 Pressure, Temperature, and pH-Monitoring Sensor; 1.2.4 Other Ingestible Sensors; 1.3 On-Chip Data-Processing Unit; 1.3.1 Image Compression; 1.3.2 Application Specific Integrated Circuit Design; 1.3.3 Radiofrequency Transmission; 1.3.4 Power Management; 1.4 Data Management of Wireless Capsule Endoscopy Systems
505 8 $a 1.5 IoT-Based Wireless Capsule Endoscopy System1.5.1 Intelligence in the System; 1.5.2 Real-Time Sensing; 1.5.3 Internet of Things Protocol; 1.5.4 Connectivity; 1.5.5 Security; 1.5.6 Improved Outcomes of Treatment; 1.6 Future Challenges; 1.7 Conclusion; References; 2 Optimization of Methods for Image-Texture Segmentation Using Ant Colony Optimization; 2.1 Introduction; 2.2 Implementation of Ant Colony Optimization Algorithm; 2.2.1 Isula Framework; 2.2.2 Ant Route Construction; 2.2.3 Ant Pheromone Update; 2.3 Image Segmentation Techniques; 2.3.1 Threshold-Based Segmentation
505 8 $a 2.3.1.1 Otsu' Algorithm2.3.1.2 Ant Colony Optimization-Based Multilevel Thresholds Selection; 2.3.1.3 Algorithm for Ant Colony Optimization; 2.3.2 Edge-Based Segmentation; 2.3.2.1 Ant Colony Optimization-Based Edge Detection Initialization; 2.3.2.2 Ant Colony Optimization-Based Structuring Process; 2.3.2.3 Ant Colony Optimization-Based Updating Process; 2.3.2.4 Decision Process; 2.4 Evaluation of Segmentation Techniques; 2.4.1 Mean-Square Error; 2.4.2 Root-Mean-Square-Error; 2.4.3 Signal-to-Noise Ratio; 2.4.4 Peak Signal-to-Noise Ratio; 2.5 Experiments and Results
505 8 $a 2.5.1 Ant Colony Optimization-Image-Segmentation Using the Isula Framework2.5.2 Performance Testing Ant Colony Optimization Image Segmentation Algorithm; 2.5.3 Application of Ant Colony Optimization on Segmentation of Brain MRI; 2.5.4 Ant Colony Optimization-Image Segmentation on Iris Images; 2.5.5 Comparison of Results; 2.6 Conclusion; References; Further Reading; 3 A Feature Fusion-Based Discriminant Learning Model for Diagnosis of Neuromuscular Disorders Using Single-Channel Needle E ... ; 3.1 Introduction; 3.2 State-of-Art-Methods; 3.3 Theoretical Modeling of Learning from Big Data
505 8 $a 3.3.1 Strategy Statement3.3.2 Discriminant Feature Fusion Framework; 3.3.3 Generalized Multidomain Learning; 3.4 Medical Measurements and Data Analysis; 3.4.1 Electromyogram Signal Recording Setup; 3.4.2 Electromyogram Datasets; 3.5Results and Discussion; 3.5.1 Correlation Analysis; 3.5.2 Performance Investigation of Discriminant Learning Scheme; 3.5.3 Comparative Study; 3.6 Conclusion; References; Further Reading; 4 Evolution of Consciousness Systems With Bacterial Behaviour; 4.1 Introduction; 4.2 Proposal; 4.2.1 Working Assumptions?; 4.2.2 Real Life Assumptions; 4.2.3 Consciousness Theory
520 $a Intelligent Data Analysis for Biomedical Applications: Challenges and Solutions presents specialized statistical, pattern recognition, machine learning, data abstraction and visualization tools for the analysis of data and discoveryof mechanisms that create data. It provides computational methods and tools for intelligent data analysis, with an emphasis on problem-solving relating to automated data collection, such as computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and more. This book provides useful references for educational institutions, industry professionals, researchers, scientists, engineers and practitioners interested in intelligent data analysis, knowledge discovery, and decision support in databases.
650 0 $a Bioinformatics. $3 583857
650 0 $a Medical sciences $x Data processing. $3 1343840
650 0 $a Data mining. $3 528622
650 0 $a Big data. $3 981821
650 1 2 $a Computational Biology. $3 581380
650 1 2 $a Medicine. $3 644133
650 7 $a COMPUTERS $x Bioinformatics. $2 bisacsh $3 1343841
655 0 $a Electronic books. $2 local $3 554714
700 1 $a Hemanth, D. Jude, $e editor. $3 1176483
700 1 $a Gupta, Deepak, $d active 2015-2016, $e editor. $3 1343839
700 1 $a Balas, Valentina Emilia, $e editor. $3 1235131
830 0 $a Intelligent data centric systems. $3 1139043
856 4 0 $u https://www.sciencedirect.com/science/book/9780128155530