Computational Intelligence and Machine Learning Approaches in Biomedical Engineering and Health Care Systems explains the emerging technology that currently drives computer-aided diagnosis, medical analysis and other electronic healthcare systems. 11 book chapters cover advances in biomedical engineering fields achieved through deep learning and soft-computing techniques. Readers are given a fresh perspective of how intelligent systems impact patient outcomes for healthcare professionals who are assisted by advanced computing algorithms.
Key Features:
- Covers emerging technologies in biomedical engineering and healthcare that assist physicians in diagnosis, treatment, and surgical planning in a multidisciplinary context
- Provides examples of technical use cases for artificial intelligence, machine learning and deep learning in medicine, with examples of different algorithms
- Introduces readers to the concept of telemedicine and electronic healthcare systems
- Provides implementations of disease prediction models for different diseases including cardiovascular diseases, diabetes and Alzheimer's disease
- Summarizes key information for learners
- Includes references for advanced readers
Table of Contents
Chapter 1 Introduction- Denoising Mri Images Using Convolutional Neural Networks
- Convolutional Neural Network For Denoising
- Building Blocks Of Convolutional Neural Network
- Network Architecture
- Implementation Platform
- Data Description
- Result And Discussion
- Quantitative Measurements
- Confusion Matrix
- Conclusion
- Consent For Publication
- Conflict Of Interest
- Acknowledgements
- References
- Introduction
- Heart
- Kidney
- Eye
- Background
- Particle Swarm Optimization Clustering
- Particle Swarm Optimization Clustering Algorithm
- Raspberry Pi
- Literature Review
- Proposed Model
- Pre-Processing
- Segmentation
- Elevated Continuous Particle Swarm Optimization Clustering
- Fitness Measures
- Feature Extraction
- Results And Discussion
- Results
- Conclusion
- Consent For Publication
- Conflict Of Interest
- Acknowledgements
- References
Chapter 3 E-Health System And Telemedicine: An Overview And Its Applications In Health Care And Medicine
- Introduction
- E-Health
- Electronic Health System
- Health Care Informatics Or Health Information Technology (Hit)
- Electronic Health Records (Ehr)
- Medical Information System
- Biomedical Informatics
- Componence Of E-Health
- Telehealth
- Real-Time Audio And Video Consultation
- Mobile-Health
- Digital Medical Imaging
- Remote Patient Monitoring (Rpm)
- Electro-Cardiogram Telemonitoring
- Blood Pressure Telemonitoring
- Glucose Level Telemonitoring
- Body Temperature Telemonitoring
- Stored And Forward
- Telemedicine
- Types Of Telemedicine Services
- Tele-Consultancy
- Tele-Emergency
- Tele-Diagnosis
- Tele-Psychiatry
- Tele-Dentistry
- Robotic Surgery
- Other Functional Systems Of E-Health System
- Clinical Ict System
- Integrated Healthcare System
- Health It Support System
- Online Health Information System
- Public Health Data Collection And Analysis
- Consumer Health Informatics Applications
- Telemedicine In Developing Countries
- Conclusion
- Consent For Publication
- Conflict Of Interest
- Acknowledgements
- References
- Introduction
- Literature Review
- Definition Of Computational Intelligence
- Definition Of Lymphatic System
- Lymphatic Treatment For Leg Pain
- Health Information Management System
- Security Issues Related To Data Breach
- Introduction To Double-Loop Learning
- Characteristics Of Double-Loop Learning
- The Approach Of Double-Loop In Patient Monitoring System
- Fuzzy Logic
- Application Of Fuzzy Logic In Patient Monitoring System
- The Proposed Approach
- Agile Model
- Agile Sdlc Implementation In Double-Loop
- Patient Monitoring System With Fuzzy Logic Implementation
- Basic Algorithm Function (Fuzzy Logic)
- Fuzzy Logic Architecture
- A. Fuzzification Module
- B. Knowledge-Based
- C. Inference Engine
- D. Defuzzification Module
- Development Of Patient Monitoring System
- A. Define Variables
- B. Construct Membership Function
- C. Construct The Base Rules
- D. Fuzzification
- E. Defuzzification
- Accuracy Of Proposed Model
- Software And Hardware Requirements
- Security Implementation In Health Monitoring System
- Digital Signature
- No Right-Click Script
- Conclusion And Future Works
- Consent For Publication
- Conflict Of Interest
- Acknowledgements
- References
- Introduction
- Literature Review
- Dataset Description
- System Architecture
- Applying The Face Mask And Safe Distance Detector
- Methodology On Face-Mask-Net Model
- Details Of Facemasknet Detection Model
- Convolutional Neural Network
- Mobilenetv2
- Learning Rate
- Social Distancing Monitoring
- Distance Measurement Using Opencv
- Social Distance Based On Yolo-V3
- Results And Discussion
- Conclusion
- Future Scope
- Consent For Publication
- Conflict Of Interest
- Acknowledgements
- References
- Introduction
- Datasets Preparation
- Pre-Processing
- Feature Extraction Techniques
- Discrete Wavelet Transformation
- Empirical Mode Decomposition
- Kth-Nearest Neighbor
- Decision Tree Classifier
- Random Forest
- Support Vector Machine
- Stochastic Gradient Descent (Sgd)
- Multi-Level Perception
- Performance Evaluation
- Accuracy
- Precision Score
- Recall Score
- F1. Score
- Results
- Ml Algorithms For Disease Prediction Using Dwt And Emd Tech, Ci And Ml, Approaches In The Field Of Bm And Hc 13
- Feature Extraction Using Dwt And Emd
- Ml Algorithms For Disease Prediction Using Dwt And Emd Tech, Ci And M, Approaches In The Field Of Bm And Hc 15
- Ml Algorithms For Disease Prediction Using Dwt And Emd Tech, Ci And Ml, Approaches In The Field Of Bm And Hc 17
- Ci And Ml Approaches In The Field Of Bm And Hc Viswavardhan Et Al.
- Ml Algorithms For Disease Prediction Using Dwt And Emd Tech, Ci And Ml, Approaches In The Field Of Bm And Hc 19
- Concluding Remarks
- Consent For Publication
- Conflict Of Interest
Author
- Parvathaneni Naga Srinivasu
- Norita Md Norwawi
- Sheng Lung Peng
