Deep Learning Techniques for Biomedical and Health Informatics
by Basant Agarwal, Valentina Emilia Balas, Lakhmi C. Jain
1st Edition
Publisher: Academic Press
Book Details
| Print ISBN | 9780128190616 |
| eText ISBN | 9780128190623 |
| Publisher | Academic Press |
| Publishing Year | 2020 |
| Edition | 1st Edition |
| Language | English |
Deep Learning Techniques for Biomedical and Health Informatics, 1st Edition, presents computational methods and their implementations across biomedical engineering and clinical practice.
The volume covers major application areas including bioinformatics for drug discovery, clinical decision support systems, and patient disease diagnosis and monitoring. It also reviews the role of algorithmic models in processing electronic health records and analyzing diagnostic imagery, highlighting specific techniques such as convolutional neural networks for lung pattern analysis.
Designed for biomedical engineers and researchers in healthcare management, intelligent systems, and data analytics, each chapter pairs introductory prerequisite methodologies with advanced techniques and critical evaluations of experimental outcomes.
Table of Contents
Part I: Deep Learning for Biomedical Engineering and Health Informatics
Chapter 1: Introduction to Deep Learning and Health Informatics
Chapter 2: A survey on deep learning algorithms for biomedical engineering
Chapter 3: Machine learning and deep learning for Biomedical and Health Informatics
Chapter 4: Deep learning for bioinformatics and drug discovery
Chapter 5: Deep learning for Clinical Decision Support Systems
Chapter 6: Deep learning for efficient Patients disease diagnosis and monitoring systems
Chapter 7: Deep learning based methods for the Prediction of disease
Chapter 8: Deep learning / Convolutional Neural Networks for Lung Pattern Analysis
Chapter 9: Recommender systems for Biomedical and Health informatics
Part II: Deep Learning and Electronics Health Records
Chapter 10: Deep Learning with Electronic Health Records (EHR)
Chapter 11: Health Data Structures and Management
Chapter 12: Deep Patient Similarity Learning with EHR
Chapter 13: Natural Language Processing, Electronic Health Records, and Clinical Research
Chapter 14: Healthcare Informatics to analyze patient health records to enable better clinical decision making and improved healthcare outcomes
Part III: Deep Learning for Medical Image Processing
Chapter 15: Machine Learning in Bio-medical Signal and Medical image processing
Chapter 16: Deep Learning for Medical Image Recognition
Chapter 17: Unsupervised Deep Feature Representations Learning for Bio-medical Image analysis
Chapter 18: Deep learning for optimizing medical big data
Chapter 19: Deep learning for Brain Image Analysis
Chapter 20: Deep Learning for Automated Brain Tumor Segmentation in MRI Images
Chapter 21: Deep Learning and the Future of Biomedical Image Analysis
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