Advances in Computer Vision and Computational Biology: Proceedings from IPCV'20, HIMS'20, BIOCOMP'20, and BIOENG'20 (Transactions on Computational Science and Computational Intelligence)

✍ Scribed by Hamid R. Arabnia (editor), Leonidas Deligiannidis (editor), Hayaru Shouno (editor), Fernando G. Tinetti (editor), Quoc-Nam Tran (editor)

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 903
• Edition: 1st ed. 2021
• Category: Library

✦ Synopsis

The book presents the proceedings of four conferences: The 24th International Conference on Image Processing, Computer Vision, & Pattern Recognition (IPCV'20), The 6th International Conference on Health Informatics and Medical Systems (HIMS'20), The 21st International Conference on Bioinformatics & Computational Biology (BIOCOMP'20), and The 6th International Conference on Biomedical Engineering and Sciences (BIOENG'20). The conferences took place in Las Vegas, NV, USA, July 27-30, 2020, and are part of the larger 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), which features 20 major tracks. Authors include academics, researchers, professionals, and students.

• Presents the proceedings of four conferences as part of the 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20);
• Includes the tracks on Image Processing, Computer Vision, & Pattern Recognition, Health Informatics & Medical Systems, Bioinformatics, Computational Biology & Biomedical Engineering;
• Features papers from IPCV'20, HIMS'20, BIOCOMP'20, and BIOENG'20.

✦ Table of Contents

Preface
Image Processing, Computer Vision, and Pattern Recognition
IPCV 2020 – Program Committee
Health Informatics & Medical Systems
HIMS 2020 – Program Committee
Bioinformatics and Computational Biology
BIOCOMP 2020 – Program Committee
Biomedical Engineering and Sciences
BIOENG 2020 – Program Committee
Contents
Part I Imaging Science and Applications of Deep Learning and Convolutional Neural Network
Evolution of Convolutional Neural Networks for Lymphoma Classification
1 Introduction
2 Related Work
2.1 Artificial Neural Networks in Medical Diagnosis
3 Approach
3.1 Hypotheses
3.2 Overview
3.3 Network Evaluation Strategy
4 Materials and Methods
4.1 Dataset
4.2 Dataset Pre-processing
4.3 Artificial Neural Networks
Feedforward Network
Convolutional Network
4.4 Evolutionary Algorithms
Algorithm Design
5 Results
5.1 Feedforward Network
K-Fold Cross-Validation and Confusion Matrix Analysis
5.2 Convolutional Network
K-Fold Cross-Validation and Confusion Matrix Analysis
5.3 Evolutionary Algorithm: Genetic Algorithm
K-Fold Cross-Validation and Confusion Matrix Analysis
5.4 Statistical Significance Testing
6 Discussion
7 Conclusion
References
Deep Convolutional Likelihood Particle Filter for Visual Tracking
1 Introduction
2 The Change of Support Problem in Convolution-Correlation Particle Filters
3 Likelihood Particle Filter
3.1 Multi-Modal Likelihood Estimation
3.2 Particle Sampling
3.3 Calculating the Weights and Posterior Distribution
4 Experimental Results
5 Conclusion
References
DeepMSRF: A Novel Deep Multimodal Speaker Recognition Framework with Feature Selection
1 Introduction
1.1 Problem Statement
1.2 Feature Selection
1.3 Contribution
2 Related Work
3 Proposed Method
3.1 Challenges
3.2 Video Speaker Recognition
3.3 Extended Video Speaker Recognition
4 Experiments
4.1 Dataset
4.2 Classifiers
4.3 VGGNET Architecture
4.4 Implementation
4.5 Ablation Study
4.6 Time Complexity
5 Future Work
6 Conclusion
References
Deep Image Watermarking with Recover Module
1 Introduction
2 Related Work
3 The Proposed Method
3.1 Approximation of JPEG Compression
3.2 Details of the Network
3.3 Loss Function
4 Experiment Result
5 Conclusion
References
Deep Learning for Plant Disease Detection
1 Introduction
2 PlantVillage Dataset
3 Deep Learning Approach
3.1 Convolutional Neural Network
3.2 Transfer Learning
4 Keras
5 Image Processing
5.1 Preprocessing
5.2 Augmentation
6 Implementation
6.1 Architectures
6.2 Training Types
6.3 Parameters
7 Results
8 Visualization
9 Future Work
9.1 Leafroll Disease
9.2 Smartphone Application
10 Conclusion
References
A Deep Learning Framework for Blended Distortion Segmentation in Stitched Images
1 Introduction
2 Method
2.1 Backbone Architecture
2.2 Region Proposal
2.3 ROI Pooling and Alignment
2.4 Box Prediction and Classification
2.5 Mask Generation
3 Experimental Results
4 Conclusion
References
Intraocular Pressure Detection Using CNN from Frontal Eye Images
1 Introduction
1.1 Background and Motivation
1.2 Related Work
2 Proposed Methodology
2.1 CNN
2.2 Dataset
2.3 Training and Test Data
3 Expected Outcome
References
Apple Leaf Disease Classification Using Superpixel and CNN
1 Introduction
2 Proposed Method
3 CNN Architecture
4 Experimental Results
5 Conclusion
References
Part II Imaging Science – Detection, Recognition, and Tracking Methods
Similar Multi-Modal Image Detection in Multi-Source Dermatoscopic Images of Cancerous Pigmented Skin Lesions
1 Introduction
2 Similar Image Detection
3 Literature Review
3.1 Intersection Distance
3.2 Bhattacharyya Distance
3.3 Chi-Square Distance
3.4 Pearson Correlation Distance
3.5 Kullback–Leibler (K–L) Distance
3.6 Earth Mover's Distance (EMD)
3.7 Methodology Comparison
4 Experimental Results
4.1 Setting the Threshold and Numerical Results
5 Conclusion and Future Work
References
Object Detection and Pose Estimation from RGB and Depth Data for Real-Time, Adaptive Robotic Grasping
1 Introduction
2 Related Work
2.1 Object Detection
2.2 Planar Pose Estimation
2.3 Adaptive Grasping
3 Method
3.1 Object Detection and Pose Estimation
Feature Extraction and Matching
Homography Estimation and Perspective Transformation
Finding Directional Vectors on the Object
Planar Pose Computation
3.2 Training Grasps for Humanoid Robots
4 Evaluation
4.1 Object Detection and Pose Estimation
4.2 Adaptive Grasping
5 Conclusion and Future Work
References
Axial Symmetry Detection Using AF8 Code
1 Introduction
2 Method
2.1 Images Processing
2.2 Contour Coding
2.3 Proposed Energy Function to Obtain the Symmetry Level
3 Results of the Method
4 Comparison
4.1 Ground Truth
4.2 Rotated Objects
4.3 Slope Chain Code
5 Advantages
6 Conclusion
References
Superpixel-Based Stereoscopic Video Saliency Detection Using Support Vector Regression Learning
1 Introduction
2 Proposed Approach
2.1 System Architecture
2.2 SLIC Superpixel Segmentation
2.3 Feature Extraction
Spatial Features
Temporal Features
Depth Features
Object Features
Spatiotemporal Features
2.4 Feature Normalization and SVR Learning
2.5 Saliency Map Refinement
3 Experimental Results
4 Concluding Remarks
References
Application of Image Processing Tools for Scene-Based Marine Debris Detection and Characterization
1 Introduction
2 Methods
2.1 Images of Floating Man-Made Debris
2.2 Image Processing
HSV Color Model
Debris Mask
Filtering Operations
Edge Detection
Blob Analysis
Statistical Computations
3 Debris Detection and Characterization Results
3.1 Case I: Multiple Submerged Floating Debris
3.2 Case II: Multiple Floating Surface Debris
3.3 Case III: Single Submerged Floating Debris
3.4 Case IV: Single Near-Surface Submerged Floating Debris
4 Discussion
5 Conclusion
References
Polyhedral Approximation for 3D Objects by Dominant PointDetection
1 Introduction
2 Proposed Method
2.1 Slice Selection and Connected Components
2.2 Selection of the Set of Dominant Points
2.3 Creation of the Polyhedron
2.4 Error Calculation
3 Experimental Results
4 Conclusion
References
Multi-Sensor Fusion Based Action Recognition in Ego-Centric Videos with Large Camera Motion
1 Introduction
2 Preliminary Experiments and Results
References
Part III Image Processing and Computer Vision – Novel Algorithms and Applications
Sensor Scheduling for Airborne Multi-target Tracking with Limited Sensor Resources
1 Overview
2 Conceptual Design
3 Sensor Scheduling
3.1 Scheduling Policies
3.2 Quality Measures and Discussion of Challenges
4 Evaluation Environment
5 Experimental Demonstration
6 Conclusion and Future Work
References
Superpixel-Based Multi-focus Image Fusion
1 Introduction
2 Proposed Approach
2.1 System Architecture
2.2 Superpixel Segmentation
2.3 Information Computation
2.4 Foreground and Background Label Estimation
2.5 Image Fusion
3 Experimental Results
4 Concluding Remarks
References
Theoretical Applications of Magnetic Fields at Tremendously Low Frequency in Remote Sensing and ElectronicActivity Classification
1 Introduction
2 The Testing Environment
2.1 The Setup
2.2 Signal Broadcast
2.3 Sensor Calibration
2.4 Ambient Collections
2.5 Data Collection and Handling
3 Data Analysis and Evaluation of Classification Algorithms
3.1 Linear Regression Analysis
3.2 T-Distributed Stochastic Neighbor Embedding (tSNE)
3.3 Dendrogram
3.4 DBSCAN
4 Summary of Results
5 Conclusions and Further Research
References
Clustering Method for Isolate Dynamic Points in Image Sequences
1 Introduction
2 Previous Works
3 Contribution
3.1 Evaluation of the Background Model
3.2 MGK Concept
3.3 MGK and A-Contrario
3.4 Klt Module
3.5 Cluster Module
4 Experience and Results
4.1 First Case: Environment with Rigid Mobile Object
4.2 Second Case: Environment with Non-rigid Mobile Objects
5 Conclusion and Future Work
References
Computer-Aided Industrial Inspection of Vehicle Mirrors Using Computer Vision Technologies
1 Introduction
2 Proposed Methods
3 Experiments and Analyses
4 Conclusions
References
Utilizing Quality Measures in Evaluating Image Encryption Methods
1 Introduction
2 Statistical Analysis Measures
2.1 Keyspace
2.2 Mean Absolute Error
2.3 MSE and PSNR
2.4 Entropy
2.5 Correlation and Neighbors Correlation
2.6 SSIM and MSSIM
2.7 Histogram Analysis
2.8 Balancedness
3 Sensitivity Analysis Measures
4 Distortion Robustness Measures
5 Complexity Analysis
6 Conclusion
References
Part IV Novel Medical Applications
Exergames for Systemic Sclerosis Rehabilitation: A Pilot Study
1 Introduction
2 Materials and Methods
2.1 ReMoVES for Remote Monitoring and Rehabilitation
2.2 Hand Exergames
2.3 Participants
2.4 Intervention
3 Experimental Results
4 Conclusion
References
Classification of Craniosynostosis Images by VigilantFeature Extraction
1 Introduction
2 Related Work
3 Our Approach
3.1 Features for ML Model
3.2 Machine Learning Model
3.3 CNN Based Model
4 Experiments
4.1 Dataset
4.2 Results and Discussion
5 Conclusion
References
DRDr: Automatic Masking of Exudates and Microaneurysms Caused by Diabetic Retinopathy Using Mask R-CNN and Transfer Learning
1 Introduction
2 Related Work
2.1 Convolutional Neural Networks
2.2 Transfer Learning
3 Methodology
3.1 Dataset
3.2 Preprocessing
3.3 Training and Implementation Details
4 Experiments and Results
5 Conclusion and Future Work
6 Conflict of Interest
References
Postoperative Hip Fracture Rehabilitation Model
1 Introduction
2 Rehabilitation Process Structure
3 Propose Rehabilitation Program
3.1 Supervised Rehabilitation at Hospital
3.2 Guided/Unsupervised Rehabilitation Exercise at Home: Living Independently
3.3 Unsupervised Rehabilitation Exercise at Outdoor Environment
4 Potential for Online Rehabilitation Program Implementation
5 Conclusion
References
ReSmart: Brain Training Games for Enhancing Cognitive Health
1 Introduction
2 Resmart
2.1 Implementation
2.2 Six Distinct Brain Training Games
3 User Study
3.1 Participants
3.2 Apparatus
3.3 Procedure
4 Discussion
5 Conclusion and Future Work
References
ActiviX: Noninvasive Solution to Mental Health
1 Introduction
2 Proposed Solution
3 User Client
4 Application Back End
5 Score Calculation
6 Communication Protocols
7 Conclusion
References
Part V Health Informatics and Medical Systems – Utilization of Machine Learning and Data Science
Visualizing and Analyzing Polynomial Curve Fitting and Forecasting of Covid Trends
1 Introduction
2 Related Work
3 Evolution
4 Polynomial Regression
5 Visualizations of Regressions
6 Finding the Best Polynomials
7 Visualizing Reconstructions Using Polynomials
8 Conclusions
References
Persuasive AI Voice-Assisted Technologies to Motivate and Encourage Physical Activity
1 Introduction
2 Motivation
3 Theoretical Background
3.1 Physical Activity and Chronic Diseases
3.2 Physical Activity and Persuasive Technologies and Systems
4 Research Approach
4.1 Persuasive Design Approach
4.2 AI VA System Design
4.3 AI VA Physical Activity Coach
4.4 Pilot Test
5 Findings and Discussion
5.1 Conclusion
References
A Proactive Approach to Combating the Opioid Crisis Using Machine Learning Techniques
Abbreviations
1 Introduction
2 Method
2.1 Data and Measures
2.2 Data Analysis
3 Results
4 Discussion
5 Conclusions
References
Security and Usability Considerations for an mHealth Application for Emergency Medical Services
1 Introduction
2 mHealth Security Challenges
2.1 Usability and Security in mHealth
2.2 HIPAA Security and Healthcare Efficiency
2.3 mHealth Security Guidance from the Office of the National Coordinator
3 Research and Design Methods
3.1 Solution Objective
3.2 Security Requirements
3.3 Security Risks and Practices
3.4 Design and Development
3.5 System Overview
3.6 Usability for Time-Critical Emergency Care
3.7 Usability and User Authentication
3.8 Encryption
3.9 Remote Device Activation and Data Wiping
3.10 Policy to Disable and/or Not Install File-Sharing Applications
3.11 Firewall and Security Software
3.12 Physical Control of Mobile Devices
3.13 Deletion of All Stored Health Information Before Discarding or Reusing the Mobile Device
4 Demonstration
5 Evaluation
5.1 Data Analysis
Efficiency
Effectiveness
Reliability
5.2 Qualitative Analysis
User Perceived Value (Satisfaction)
Learnability (Ease of Use)
6 Discussion
6.1 A Heuristic for Security Implementation
6.2 Security Context: Extending the Security Heuristic for Time- and Information-Critical Systems
7 Conclusion
References
Semantic Tree Driven Thyroid Ultrasound Report Generation by Voice Input
1 Introduction
2 Methodology
2.1 Overview
2.2 Semantic Tree
2.3 Algorithms
TIG
TTT
3 Experimental Results and Analysis
3.1 Experimental Setup
3.2 Experimental Results
The Character Ratio
The Accuracy of the Semantic Tree Instance
BLEU
Subjective Evaluation
4 Conclusion and Future Work
References
Internet-of-Things Management of Hospital Beds for Bed-RestPatients
1 Introduction
2 Bed-Rest Management
3 Components
3.1 Sensors
3.2 Microcontroller
3.3 Network
3.4 Server
3.5 Mobile Devices and Mobile Application
4 Initial System
5 Conclusion and Future Work
References
Predicting Length of Stay for COPD Patients with Generalized Linear Models and Random Forests
1 Introduction
2 Data Processing and Methodology
2.1 Data Set
2.2 Preliminary Selection of Predictor Variables and Missing Values Analysis
2.3 Variable Selection and Model Development
3 Results and Discussion
References
Predicting Seizure-Like Activity Using Sensors from Smart Glasses
1 Introduction
2 Smart Glasses and Data Collection
3 Deep Neural Network (DNN)
4 Training Results
5 Summary and Future Work
References
Epileptic iEEG Signal Classification Using Pre-trained Networks
1 Introduction
2 Spectrogram of Medical Signals and Convolutional Neural Network
3 Performance Results
4 Summary
5 Future Work
References
Seizure Prediction and Heart Rate Oscillations Classification in Partial Epilepsy
1 Introduction
2 ECG Data Description and Visualization
3 Methodology and Feature Extraction
3.1 Inter-Beat Intervals Features
3.2 Segmentation and RR Interval Features
3.3 Wavelet Features and Background on Wavelet Transform
4 Recurrent Neural Network (RNN)
5 Long Short-Term Memory (LSTM)
6 Performance results
7 Conclusion
References
A Comparative Study of Machine Learning Models for Tabular Data Through Challenge of Monitoring Parkinson's Disease Progression Using Voice Recordings
1 Introduction
1.1 Dataset
1.2 Document Organization
2 Related Work
3 Machine Learning Strategies and Our Research Road Map
3.1 Feature Selection
3.2 Regression-Based Methods
3.3 Instance-Based Learning
3.4 Ensemble Methods
3.5 Verification
3.6 Classification by Discretization
3.7 Multi-Instance Learning
4 Discussion and Conclusion
References
ICT and the Environment: Strategies to Tackle Environmental Challenges in Nigeria
1 Introduction
2 ICT and Economy Growth in Nigeria
3 Types of Pollution and Environmental Issues in Nigeria
3.1 Water Pollution
3.2 Air Pollution
3.3 Land Pollution and Heavy Metals
4 Potential Roles of ICT in Tackling Environmental Challenges
4.1 ICT Services for Environmental Observations: Satellite Observations and Direct Sensors
4.2 ICT Services for Environmental Analysis: Grid Computing and GIS Systems
4.3 ICT for Environment Planning, Management and Protection, Mitigation and Capacity Building for Environmental Sustainability
5 Conclusions and Recommendations
References
Conceptual Design and Prototyping for a Primate Health History Knowledge Model
1 Introduction
2 Data Needs and Conceptual Data Models
2.1 Unified Coding Scheme
3 Use Cases and Application Design Concepts
4 Database and Application Prototyping
5 Conclusions and Future Work
References
Implementation of a Medical Data Warehouse Framework to Support Decisions
1 Introduction
2 Material and Method
2.1 Data Warehouse System
2.2 Implementation Tools
2.3 Medical Analytical Framework
3 Results
3.1 Medical Operational Data Store
3.2 Star Schemas
3.3 ETL Tools
3.4 OLAP Server
3.5 Analyses
3.6 Validation of the MAF
4 Conclusions
References
Personalization of Proposed Services in a Sensor-Based Remote Care Application
1 Introduction
2 Related Works
3 Functional Architecture of the System
4 Services Personalization
4.1 Patient's Profile
4.2 Services Model
4.3 Personalization of Services
5 Exploitation of Services
5.1 Object Management
5.2 Services Exploitation Scenario
6 Conclusion
References
A Cross-Blockchain Approach to Emergency Medical Information
1 Introduction
2 A Permissioned Blockchain Technology (HLF)
3 Related Work
3.1 Fast Healthcare Interoperability Resource (FHIR)
Challenges with FHIR
3.2 Inter-blockchain Communication
4 Our Approach
5 Our Challenges
6 Conclusion
7 Future Direction
References
Robotic Process Automation-Based Glaucoma Screening System: A Framework
1 Introduction
2 The RPA-Based Glaucoma Screening System
2.1 Design of the Screening System
2.2 User Interface
2.3 Machine Learning-Based Analysis
3 Discussions
4 Conclusion
References
Introducing a Conceptual Framework for Architecting Healthcare 4.0 Systems
1 Introduction
2 Relevant Theoretical Concepts
2.1 Apache Kafka
2.2 Challenges in Building Data Integration Systems
3 A Conceptual Framework for Architecting Healthcare 4.0 Applications
4 Related Work
5 Conclusions and Further Directions
References
A Machine Learning-Driven Approach to Predict the Outcome of Prostate Biopsy: Identifying Cancer, Clinically Significant Disease, and Unfavorable Pathological Features on Prostate Biopsy
1 Introduction
2 Methods
2.1 Study Population
2.2 Outcome and Study Design
2.3 Statistical Analysis
3 Results
3.1 Study Population Characteristics
3.2 Prediction of Prostate Cancer, Significant Disease, and Unfavorable Pathology
4 Discussion
5 Conclusions
References
Using Natural Language Processing to Optimize Engagement of Those with Behavioral Health Conditions that Worsen Chronic Medical Disease
1 Introduction
2 Natural Language Processing Tasks
2.1 Syntactic Analysis
2.2 Semantic Analysis
3 Data Collection and Characteristics
4 Methodology
5 Results
6 Conclusion
References
Smart Healthcare Monitoring Apps with a Flavorof Systems Engineering
1 Introduction
2 Proposed Ideas
2.1 Causal Model
2.2 System Dynamics Model
3 Expected Outcome
References
Using Artificial Intelligence for Medical Condition Prediction and Decision-Making for COVID-19 Patients
1 Introduction and Background
2 Data Processing and Predictive Analytics
2.1 Dataset
2.2 Data Processing
2.3 Machine Learning and Predictive Analytics Algorithms
2.4 Evaluation
3 Results
References
An Altmetric Study on Dental Informatics
1 Introduction
1.1 Definition of Dental Informatics
1.2 Altmetric Attention Score and Altmetric Explorer
2 Literature Review
2.1 Dental Informatics
2.2 Dental Informatics Challenges
2.3 Support Systems
2.4 Doctor-Patient Relationship
2.5 Ontology in Dental Informatics
2.6 Applications of Dental Ontologies
2.7 Major Research Areas in Dental Informatics
Training and Education
Compliance and Legal Issues
Evidence-Based Dentistry
3 Method
3.1 Dataset
3.2 Procedure
Step 1. Determine Seed Query Keywords
Step 2. Search and Download Raw Data
Step 3. Data Clean-Up
4 Results
4.1 Attention Score
4.2 Timeline for Mentions
4.3 Twitter Demographics by Countries
4.4 Top Ten Journals for Dental Informatics
4.5 Frequency of Top Five Mention Categories
4.6 Publications per Year
4.7 Top 15 Publication Affiliations
5 Discussion and Conclusion
References
Part VI Bioinformatics & Computational Biology – Applications and Novel Frameworks
A Novel Method for the Inverse QSAR/QSPR to Monocyclic Chemical Compounds Based on Artificial Neural Networks and Integer Programming
1 Introduction
2 Preliminary
3 A Method for Inferring Chemical Graphs
4 MILPs for Monocyclic Chemical Graphs
5 Experimental Results
6 Concluding Remarks
References
Predicting Targets for Genome Editing with Long Short Term Memory Networks
1 Introduction
2 Prior Work
3 Materials and Methods
3.1 Data Collection
3.2 Sequence Encoding and Feature Engineering
3.3 Long Short Term Memory Network
3.4 Classical Machine Learning Models
3.5 Validation Protocol and Performance Measurements
4 Results
5 Conclusion
References
MinCNE: Identifying Conserved Noncoding Elements Using Min-Wise Hashing
1 Introduction
2 Materials and Methods
2.1 Minhash Signatures
2.2 LSH-Based Clustering
2.3 CNE Identification
2.4 Benchmark Dataset
2.5 Performance Evaluation
3 Results and Discussion
3.1 CNE Identification Performance
3.2 Time and Space Usage
4 Conclusion
References
An Investigation in Optimal Encoding of Protein Primary Sequence for Structure Prediction by Artificial Neural Networks
1 Introduction
2 Background and Method
2.1 Protein Structure Formation in Rotamer Space
2.2 Methodology
2.3 The Explored Encoding Schemes
2.4 Target Proteins
2.5 Data Processing
2.6 Artificial Neural Network Architectures
2.7 Training, Testing, and Evaluation Protocols
3 Results and Discussion
3.1 Root Mean Squared Error Versus Mean Absolute Error
3.2 Optimal Architecture
3.3 Encoding and Window Size
3.4 Expanded CATH Selection
3.5 Overall Performance
4 Conclusions and Future Work
References
Rotation-Invariant Palm ROI Extraction for Contactless Recognition
1 Introduction
2 Related Works
3 Proposed Palm ROI Extraction Method
3.1 Hand Segmentation
3.2 Finding and Correcting Convex Hull
3.3 Finding Key Vector Candidates
3.4 Optimal Key Vector Selection
3.5 ROI Extraction
4 Experiments and Discussion
4.1 Performance Evaluation on Tongji Contactless Palm Vein Dataset
4.2 Performance Evaluation on a Self-Collected Palm Print Dataset
5 Conclusion
References
Mathematical Modeling and Computer Simulations of Cancer Chemotherapy
1 Introduction
2 The Cancer Chemotherapy Model
2.1 Definition of Variables, Parameters, Rate Constants, and Auxiliary Functions
2.2 The Model Equations
2.3 The Basic Cancer Chemotherapy Model for Solid Tumors
3 Theoretical Analysis of No-Treatment Case
3.1 Existence of Non-negative Solutions
3.2 Model for No-Treatment Case and Analysis of Equilibrium Points
4 Theoretical Analysis of Continuous Intravenous Infusion Case
4.1 Model for Continuous Intravenous Infusion Case
4.2 Analysis of E3 == [ 0mu mumu xxequationx1,0,0mu mumu xxequationx3 ]
5 Computer Simulations
5.1 Simulation #1 – No-Treatment Case
5.2 Simulation #2 – High-Dose Chemotherapy
5.3 Simulation #3 – Therapeutic Failure
5.4 Simulation #4 – Chemotherapy wth Stealth Liposome
6 Summary
References
Optimizing the Removal of Fluorescence and Shot Noise in Raman Spectra of Breast Tissue by ANFIS and Moving Averages Filter
1 Introduction
2 Materials and Methods
2.1 ANFIS (Adaptative Neuro-Fuzzy Inference System)
2.2 Moving Averages
2.3 Parallel Computing
3 Experiments
4 Results and Discussion
4.1 Description of the Proposed Algorithm for Fluorescence and Shot Noise Reduction
4.2 Healthy Breast Tissue and Damaged Breast Tissue: Morphology and Chemistry
4.3 Optimum Design in the Removal of Fluorescence and Shot Noises in Raman Spectrum of Healthy and Damaged Breast Tissues
5 Conclusions
References
Re-ranking of Computational Protein–Peptide Docking Solutions with Amino Acid Profiles of Rigid-Body Docking Results
1 Introduction
2 Materials and Methods
2.1 Protein–Peptide Docking Re-ranking
2.2 Dataset
2.3 Evaluation of Prediction Performance
3 Results and Discussion
3.1 CABS-Dock and Re-ranking Results
3.2 Example of Predicted Structures
4 Conclusion
References
Structural Exploration of Rift Valley Fever Virus L Protein Domain in Implicit and Explicit Solvents by Molecular Dynamics
1 Introduction
2 Methods
2.1 Details of the Simulations
3 Results and Discussion
3.1 Properties of All-Atom MD-Simulated Solvents
3.2 Analysis of Dictionary of Secondary Structures of Proteins (DSSP)
3.3 Structural Properties and Energetics of the Peptide from MD Simulations
3.4 Cluster Analysis of the MD Trajectory of the RVFV L Protein Peptide
4 Conclusions
References
Common Motifs in KEGG Cancer Pathways
1 Introduction
2 Materials and Methods
3 Results and Discussions
4 Conclusion
References
Phenome to Genome – Application of GWAS to Asthmatic Lung Biomarker Gene Variants
1 Introduction
1.1 Recent Literature Review
2 Methods
3 Results
4 Discussion
5 Conclusion
References
Cancer Gene Diagnosis of 84 Microarrays Using Rank of 100-Fold Cross-Validation
1 Introduction
2 Material
2.1 Alon et al. Microarray (Alon Data)
2.2 Gene Diagnosis by Alon Data
Two Universal Data Structure of LSD
Difficulty of SM Analysis
Breakthrough of RIP Discriminant Scores and Signal Data
2.3 Materials in This Research
3 Theory
3.1 Purpose of Research and Six MP-based LDFs
3.2 Internal and External Checks, LOO and k-fold CV LDFs
3.3 100-Fold Cross-Validation (Method2)
4 Result
4.1 Validation of 64 SMs by M2
4.2 Evaluation of the Worst SM64 by 100-Fold Cross-Validation
4.3 Validation of 129 BGSs by Method1
5 Discussion
5.1 Two Universal Data Structures of LSD
5.2 Comparison of Three Types of Research
Medical Research
Statistical Approach
Machine Learning
6 Conclusion
References
A New Literature-Based Discovery (LBD) Application Using the PubMed Database
1 Introduction
2 Implementation
3 Conclusions
References
An Agile Pipeline for RNA-Seq Data Analysis
1 Introduction
2 Methods
2.1 Overview of RNAseq Pipeline
2.2 Benefits of Uniform Environments
2.3 Challenges of Docker and Containerization
2.4 Hardware Configuration
2.5 -12pt-3pc
References
Part VII Biomedical Engineering and Applications
Stage Classification of Neuropsychological Tests Based on Decision Fusion
1 Introduction
2 Late Fusion Methods
2.1 Dempster-Shafer Combination
2.2 Alpha Integration
2.3 Copulas
2.4 Independent Component Analysis Mixture Model
2.5 Behavior Knowledge Space
3 Experiments
4 Results and Discussion
5 Conclusions
References
An Investigation of Texture Features Based on Polyp Size for Computer-Aided Diagnosis of Colonic Polyps
1 Introduction
2 Materials and Methods
2.1 Flowchart of Our Method
2.2 Malignancy Risk of the Polyps
2.3 Data Preparation
3 Results
4 Discussion and Conclusions
References
Electrocardiogram Classification Using Long Short-Term Memory Networks
1 Introduction
2 Methodology
2.1 Feature Extraction of ECG Signals
2.2 Method
2.3 LSTM Recurrent Network
3 Experimental Results
3.1 Experiment Setup
3.2 Materials
3.3 Evaluation
3.4 Results
4 Conclusions
References
Cancer Gene Diagnosis of 78 Microarrays Registered on GSE from 2007 to 2017
1 Introduction
2 Material
3 Method
3.1 Revised IP-OLDF and Hard-Margin SVM
3.2 Small Matryoshka and Basic Gene Set Decomposition
3.3 The 100-Fold Cross-Validation for Small Sample
4 Result
4.1 Summary of Our Research (Three Studies)
4.2 Confirmation of LSD and Decomposition of Ten SMs: (Study1)
4.3 Validations of SMs and BGSs of Breast5 by Method1: (Study 2)
4.4 Validations of the Best BGS71 of Breast5: Study3
4.5 Validations of the Worst BGS43 of Breast5: Study3
5 Discussion
5.1 SM and BGS Decomposition of High-Dimensional Gene Data
5.2 Successful Feature Selection Methods by iPS Research
5.3 Hierarchical Structure of Number of Misclassification
The NMs by RIP, H-SVM, Logistic Regression, Fisher's LDF, and QDF
Hierarchical Reliability Categories of NM by Discriminant Functions
6 Conclusion
References
Index