Deep Learning Techniques for Biomedical and Health Informatics

Deep Learning Techniques for Biomedical and Health Informatics, authored by Basant Agarwal, offers a comprehensive overview of the state-of-the-art deep learning-based methods for biomedical and health informatics. This book not only covers the best-performing methods but also provides detailed implementation methodologies, making it an essential resource for new researchers and practitioners.

Applications in Biomedical Engineering and Health Informatics

The book explores a wide range of deep learning applications for biomedical engineering and health informatics, including:

• Deep Learning for drug discovery
• Clinical decision support systems
• Disease diagnosis, prediction, and monitoring

Deep Learning in Electronic Health Records (EHR)

Deep Learning Techniques for Biomedical and Health Informatics also delves into the application of deep learning in electronic health records, covering topics such as:

• Health data structures and management
• Deep patient similarity learning
• Natural language processing
• Improving clinical decision-making

Deep Learning for Medical Image Processing

The book provides detailed coverage of deep learning for medical image processing, including:

• Optimizing medical big data
• Brain image analysis
• Brain tumor segmentation in MRI imaging
• The future of biomedical image analysis

Deep Learning Techniques for Biomedical and Health Informatics is an indispensable resource for researchers, practitioners, and students seeking to understand the latest advancements in deep learning for biomedical and health informatics.