Deep Learning Techniques for Biomedical and Health Informatics

Basant Agarwal,Valentina Emilia Balas,Lakhmi C. Jain,Ramesh Chandra Poonia,Manisha Sharma

• Verlag: Academic Press
• Jahr: 2020
• ISBN:
  9780128190623
• Thema: Scienze biologiche
• Thema: Biotecnologia

Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners 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 Biomedical Engineering, Electronic Health Records, and medical image processing.

• Examines 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
• Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making
• Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis

Inhaltsverzeichnis

• Cover image
• Title page
• Table of Contents
• Copyright
• Contributors
• 1: Unified neural architecture for drug, disease, and clinical entity recognition
• 2: Simulation on real time monitoring for user healthcare information
• 3: Multimodality medical image retrieval using convolutional neural network
• 4: A systematic approach for identification of tumor regions in the human brain through HARIS algorithm
• 5: Development of a fuzzy decision support system to deal with uncertainties in working posture analysis using rapid upper limb assessment
• 6: Short PCG classification based on deep learning
• 7: Development of a laboratory medical algorithm for simultaneous detection and counting of erythrocytes and leukocytes in digital images of a blood smear
• 8: Deep learning techniques for optimizing medical big data
• 9: Simulation of biomedical signals and images using Monte Carlo methods for training of deep learning networks
• 10: Deep learning-based histopathological image analysis for automated detection and staging of melanoma
• 11: Potential proposal to improve data transmission in healthcare systems
• 12: Transferable approach for cardiac disease classification using deep learning
• 13: Automated neuroscience decision support framework
• 14: Diabetes prediction using artificial neural network
• Index