Basant Agarwal, Valentina E. Balas, Lakhmi C. Jain, Ramesh Chandra Poonia, Manisha Sharma
Readers of the Deep Learning Techniques for Biomedical and Health Informatics (PDF) will gain an understanding of the most recent advancements that have been made in the field of deep learning-based methods for biomedical and health informatics. Not only does this ebook discuss the most effective ways, but it also gives methods for putting those methods into practice. This e-book incorporates all of the necessary procedures into each individual chapter, making it a very valuable resource for both novice practitioners and scholars. The chapters progress from the most fundamental methodology to the most advanced methodologies, including comprehensive critical discussions on experimental results and detailed descriptions of proposed approaches, as well as how these can be applied to electronic health records, biomedical engineering, and medical image processing.
- Covers Deep Learning in medical image processing in great detail, including analysis of the brain and brain tumors using MRI, as well as optimizing medical large data and discussing the future of biomedical image analysis.
- Explores a diverse range of applications of Deep Learning in the fields of Biomedical Engineering and Health Informatics, including clinical decision support systems, Deep Learning for drug discovery, prediction and monitoring, and illness detection.
- The application of Deep Learning to Electronic Health Records (EHR) is discussed, along with related topics such as health data formats and management, natural language processing, deep patient similarity learning, and ways to improve clinical decision-making.
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