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Deep Learning Techniques for Biomedical and Health Informatics – eBook

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eBook details

  • Authors: Basant Agarwal, Valentina E. Balas, Lakhmi C. Jain, Ramesh Chandra Poonia, Manisha Sharma
  • File Size: 36 MB
  • Format: PDF
  • Length: 625 pages
  • Publisher: Academic Press
  • Publication Date: January 14, 2020
  • Language: English
  • ASIN: B083QBPJF1
  • ISBN-10: 0128190612, 0128190620
  • ISBN-13: 9780128190616, 9780128190623

$104.78 $20.00

Product ID: 106565 SKU: deep-learning-techniques-for-biomedical-and-health-informatics-pdf Categories: , , , , Tags: , ,

Deep Learning Techniques for Biomedical and Health Informatics (PDF) provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. This ebook covers not only the best-performing methods, it also presents implementation methods. The ebook includes all the prerequisite methodologies in every chapter so that new practitioners and researchers will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they are applied to Electronic Health Records, Biomedical Engineering, and medical image processing.

  • Provides detailed coverage of Deep Learning for medical image processing, including brain image analysis, brain tumor segmentation in MRI imaging, optimizing medical big data, and the future of biomedical image analysis
  • Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including clinical decision support systems, Deep Learning for drug discovery, prediction and monitoring, disease diagnosis
  • Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, natural language processing, deep patient similarity learning, and how to improve clinical decision-making

NOTE: This sale only includes the ebook Deep Learning Techniques for Biomedical and Health Informatics in PDF. No access codes included.

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