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The book is a baseline reference for researchers and academicians who are investigating the application of deep learning algorithms in the healthcare sector. It focuses on medical imaging and healthcare data analytics.
The book is a baseline reference for researchers and academicians who are investigating the application of deep learning algorithms in the healthcare sector. It focuses on medical imaging and healthcare data analytics.
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Autorenporträt
Dr. K. Murugeswari is a Senior Assistant Professor in the School of Computing Science and Engineering at VIT Bhopal University, M.P, India. Dr. B. Sundaravadivazhagan is a professor in the Department of Information Technology at the University of Technology and Applied Science-AL Mussanah in Oman. Dr. S. Poonkuntran is a Professor and Dean in the School of Computing Science and Engineering at VIT Bhopal Uniersity, M.P, India. Dr. Thendral Puyalnithi is an Assistant Professor Senior in the Mepco Schlenk Engineering College in the Department of Artificial Intelligence and Data Science, Tamil Nadu, India.
Inhaltsangabe
Preface. List of Contributors. Chapter 1 Deep Learning in Healthcare and Clinical Studies. Chapter 2 Deep Learning Framework for Classification of Healthcare Data. Chapter 3 Leveraging Deep Learning in Hate Speech Analysis on Social Platform. Chapter 4 Medical Image Analysis Based on Deep Learning Approach for Early Diagnosis of Diseases. Chapter 5 A Study of Medical Image Analysis using Deep Learning Approaches. Chapter 6 Deep Learning for Designing Heuristic Methods for Healthcare Data Analytics. Chapter 7 Deep Learning-Based Smart Healthcare System for Patient's Discomfort Detection. Chapter 8 Gesture Identification for Hearing-Impaired through Deep Learning. Chapter 9 Deep Learning-Based Cloud Computing Technique for Patient Data Management. Chapter 10 Challenges and Issues in Health Care and Clinical Studies Using Deep Learning. Chapter 11 Protecting Medical Images Using Deep Learning Fuzzy Extractor Model. Chapter 12 Review of Various Deep Learning Techniques with a Case Study on Prognosticate Diagnostics of Liver Infection. Chapter 13 Case Study: Application of Ensemble Classifier for Diabetes Healthcare Data Analytics. Chapter 14 Deep Convolutional Neural Network Models for Early Detection of Breast Cancer from Digital Mammograms. Chapter 15 Case Study: Deep Learning-Based Approach for Detection and Treatment of Retinopathy of Prematurity. Index.
Preface. List of Contributors. Chapter 1 Deep Learning in Healthcare and Clinical Studies. Chapter 2 Deep Learning Framework for Classification of Healthcare Data. Chapter 3 Leveraging Deep Learning in Hate Speech Analysis on Social Platform. Chapter 4 Medical Image Analysis Based on Deep Learning Approach for Early Diagnosis of Diseases. Chapter 5 A Study of Medical Image Analysis using Deep Learning Approaches. Chapter 6 Deep Learning for Designing Heuristic Methods for Healthcare Data Analytics. Chapter 7 Deep Learning-Based Smart Healthcare System for Patient's Discomfort Detection. Chapter 8 Gesture Identification for Hearing-Impaired through Deep Learning. Chapter 9 Deep Learning-Based Cloud Computing Technique for Patient Data Management. Chapter 10 Challenges and Issues in Health Care and Clinical Studies Using Deep Learning. Chapter 11 Protecting Medical Images Using Deep Learning Fuzzy Extractor Model. Chapter 12 Review of Various Deep Learning Techniques with a Case Study on Prognosticate Diagnostics of Liver Infection. Chapter 13 Case Study: Application of Ensemble Classifier for Diabetes Healthcare Data Analytics. Chapter 14 Deep Convolutional Neural Network Models for Early Detection of Breast Cancer from Digital Mammograms. Chapter 15 Case Study: Deep Learning-Based Approach for Detection and Treatment of Retinopathy of Prematurity. Index.
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