Data Analytics in Bioinformatics. Группа авторов
Читать онлайн книгу.
Machine Learning 8.4 Feature Engineering 8.5 Methodology 8.6 Result Analysis 8.7 Conclusion References 9 A Comprehensive Study on the Application of Grey Wolf Optimization for Microarray Data 9.1 Introduction 9.2 Microarray Data 9.3 Grey Wolf Optimization (GWO) Algorithm 9.4 Studies on GWO Variants 9.5 Application of GWO in Medical Domain 9.6 Application of GWO in Microarray Data 9.7 Conclusion and Future Work References 10 The Cluster Analysis and Feature Selection: Perspective of Machine Learning and Image Processing 10.1 Introduction 10.2 Various Image Segmentation Techniques 10.3 How to Deal With Image Dataset 10.4 Class Imbalance Problem 10.5 Optimization of Hyperparameter 10.6 Case Study 10.7 Using AI to Detect Coronavirus 10.8 Using Artificial Intelligence (AI), CT Scan and X-Ray 274 10.9 Conclusion References
8
Part 3: MACHINE LEARNING AND HEALTHCARE APPLICATIONS
11 Artificial Intelligence and Machine Learning for Healthcare Solutions
11.1 Introduction
11.2 Using Machine Learning Approaches for Different Purposes
11.3 Various Resources of Medical Data Set for Research
11.4 Deep Learning in Healthcare
11.5 Various Projects in Medical Imaging and Diagnostics
11.6 Conclusion
References
12 Forecasting of Novel Corona Virus Disease (Covid-19) Using LSTM and XG Boosting Algorithms
12.1 Introduction
12.2 Machine Learning Algorithms for Forecasting 296
12.3 Proposed Method
12.4 Implementation
12.5 Results and Discussion
12.6 Conclusion and Future Work
References
13 An Innovative Machine Learning Approach to Diagnose Cancer at Early Stage
13.1 Introduction
13.2 Related Work
13.3 Materials and Methods
13.4 System Design
13.5 Results and Discussion
13.6 Conclusion
References
14 A Study of Human Sleep Staging Behavior Based on Polysomnography Using Machine Learning Techniques
14.1 Introduction
14.2 Polysomnography Signal Analysis
14.3 Case Study on Automated Sleep Stage Scoring
14.4 Summary and Conclusion
References
15 Detection of Schizophrenia Using EEG Signals
15.1 Introduction
15.2 Methodology
15.3 Literature Review
15.4 Discussion
15.5 Conclusion
References
16 Performance Analysis of Signal Processing Techniques in Bioinformatics for Medical Applications Using Machine Learning Concepts
16.1 Introduction
16.2 Basic Definition of Anatomy and Cell at Micro Level 397
16.3 Signal Processing—Genome Signal Processing 403
16.4 Hotspots Identification Algorithm
16.5 Results—Experimental Investigations
16.6 Analysis Using Machine Learning Metrics
16.7 Conclusion
Appendix
A.1 Hotspot Identification Code
A.2 Performance Metrics Code
References
17 Survey of Various Statistical Numerical and Machine Learning Ontological Models on Infectious Disease Ontology
17.1