Healthcare Analytics -

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Résumé :
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Biographie:

List of Contributors xvii
Preface xxi

Part I Advances In Biomedical And Health Informatics 1

1 Recent Development in Methodology for Gene Network Problems and Inferences 3
Sung W. Han and Hua Zhong

1.1 Introduction 3
1.2 Background 5
1.3 Genetic Data Available 7
1.4 Methodology 7
1.5 Search Algorithm 13
1.6 PC Algorithm 15
1.7 Application/Case Studies 16
1.8 Discussion 23
1.9 Other Useful Softwares 23

2 Biomedical Analytics and Morphoproteomics: An Integrative Approach for Medical Decision Making for Recurrent or Refractory Cancers 31
Mary F. McGuire and Robert E. Brown

2.1 Introduction 31
2.2 Background 32
2.2.1 Data 33
2.2.2 Tools 33
2.2.3 Algorithms 34
2.2.4 Literature Review 35
2.3 Methodology 37
2.3.1 Morphoproteomics (Fig. 2.1(1-3)) 39
2.3.2 Biomedical Analytics (Fig. 2.1(4-10)) 40
2.3.3 Integrating Morphoproteomics and Biomedical Analytics 44
2.4 Case Studies 46
2.4.1 Clinical: Therapeutic Recommendations for Pancreatic Adenocarcinoma 46
2.4.2 Clinical: Biology Underlying Exceptional Responder in Refractory Hodgkin's Lymphoma 48
2.4.3 Research: Role of the Hypoxia Pathway in Both Oncogenesis and Embryogenesis 50
2.5 Discussion 51
2.6 Conclusions 52

3 Characterization and Monitoring of Nonlinear Dynamics and Chaos in Complex Physiological Systems 59
Hui Yang, Yun Chen, and Fabio Leonelli
3.1 Introduction 59
3.2 Background 61
3.3 Sensor-Based Characterization and Modeling of Nonlinear Dynamics 65
3.3.1 Multifractal Spectrum Analysis of Nonlinear Time Series 65
3.3.2 Recurrence Quantification Analysis 75
3.3.3 Multiscale Recurrence Quantification Analysis 78
3.4 Healthcare Applications 80
3.4.1 Nonlinear Characterization of Heart Rate Variability 81
3.4.2 Multiscale Recurrence Analysis of Space-Time Physiological Signals 85
3.5 Summary 88

4 Statistical Modeling of Electrocardiography Signal for Subject Monitoring and Diagnosis 95
Lili Chen, Changyue Song, and Xi Zhang

4.1 Introduction 95
4.2 Basic Elements of ECG 96
4.3 Statistical Modeling of ECG for Disease Diagnosis 99
4.3.1 ECG Signal Denoising 100
4.3.2 Waveform Detection 105
4.3.3 Feature Extraction 106
4.3.4 Disease Classification and Diagnosis 111
4.4 An Example: Detection of Obstructive Sleep Apnea from a Single ECG Lead 115
4.4.1 Introduction to Obstructive Sleep Apnea 115
4.5 Materials and Methods 115
4.5.1 Database 115
4.5.2 QRS Detection and RR Correction 116
4.5.3 R Wave Amplitudes and EDR Signal 117
4.5.4 Feature Set 117
4.5.5 Classifier Training with Feature Selection 118
4.6 Results 118
4.6.1 QRS Detection and RR Correction 118
4.6.2 Feature Selection 118
4.6.3 OSA Detection 120
4.7 Conclusions and Discussions 121

5 Modeling and Simulation of Measurement Uncertainty in Clinical Laboratories 127
Varun Ramamohan, James T. Abbott, and Yuehwern Yih

5.1 Introduction 127
5.2 Background and Literature Review 129
5.2.1 Measurement Uncertainty: Background and Analytical Estimation 130
5.2.2 Uncertainty in Clinical Laboratories 134
5.2.3 Uncertainty in Clinical Laboratories: A System Approach 136
5.3 Model Development Guidelines 138
5.3.1 System Description and Process Phases 138
5.3.2 Modeling Guidelines 139
5.4 Implementation of Guidelines: Enzyme Assay Uncertainty Model 141
5.4.1 Calibration Phase 142
5.4.2 Sample Analysis Phase 149
5.4.3 Results and Analysis 150
5.5 Discussion and Conclusions 152

6 Predictive Analytics: Classif...