1st Edition
Deep Learning for Smart Healthcare Trends, Challenges and Applications
Deep learning can provide more accurate results compared to machine learning. It uses layered algorithmic architecture to analyze data. It produces more accurate results since learning from previous results enhances its ability. The multi-layered nature of deep learning systems has the potential to classify subtle abnormalities in medical images, clustering patients with similar characteristics into risk-based cohorts, or highlighting relationships between symptoms and outcomes within vast quantities of unstructured data.
Exploring this potential, Deep Learning for Smart Healthcare: Trends, Challenges and Applications is a reference work for researchers and academicians who are seeking new ways to apply deep learning algorithms in healthcare, including medical imaging and healthcare data analytics. It covers how deep learning can analyze a patient’s medical history efficiently to aid in recommending drugs and dosages. It discusses how deep learning can be applied to CT scans, MRI scans and ECGs to diagnose diseases. Other deep learning applications explored are extending the scope of patient record management, pain assessment, new drug design and managing the clinical trial process.
Bringing together a wide range of research domains, this book can help to develop breakthrough applications for improving healthcare management and patient outcomes.
Preface
List of Contributors
Chapter 1 Deep Learning in Healthcare and Clinical Studies
V. Pandimurugan, S. Angayarkanni Annamalai, G. Saranya, V. Rajaram, and A. Chinnasamy
Chapter 2 Deep Learning Framework for Classification of Healthcare Data
Hannah Vijaykumar, K. Maheswari, and S. Vahini Ezhilraman
Chapter 3 Leveraging Deep Learning in Hate Speech Analysis on Social Platform
R. Manikandan, S. Hariharasitaraman, S. Ramkumar, and R. Gobinath
Chapter 4 Medical Image Analysis Based on Deep Learning Approach for Early Diagnosis of Diseases
S. Balasubramaniam, A. Prasanth, K. Satheesh Kumar, and Kavitha V.
Chapter 5 A Study of Medical Image Analysis using Deep Learning Approaches
Syed Saba Raoof, M. A. Saleem Durai, C. Srimathi, Robin Doss, and M. A. Mohammed Sahul Hameed
Chapter 6 Deep Learning for Designing Heuristic Methods for Healthcare Data Analytics
J. Joselin, V.S. Anita Sofia, S. Dhanalakshmi, and S. Indhumathi
Chapter 7 Deep Learning-Based Smart Healthcare System for Patient’s Discomfort Detection
J. Antony Vijay, B. Gomathi, M. Mythily, and Beaulah David
Chapter 8 Gesture Identification for Hearing-Impaired through Deep Learning
M. Maragatharajan, S.P. Balakannan, C. Balasubramanian, and P. Naveen
Chapter 9 Deep Learning-Based Cloud Computing Technique for Patient Data Management
K.E. Hemapriya and S. Saraswathi
Chapter 10 Challenges and Issues in Health Care and Clinical Studies Using Deep Learning
M. Renuka Devi, V. Sindhu, and S. Devi
Chapter 11 Protecting Medical Images Using Deep Learning Fuzzy Extractor Model
S. Aanjan Kumar, P. Karthikeyan, S. Aanjana Devi, S. Poonkuntran, V. Palanisamy, and V. Navatharani
Chapter 12 Review of Various Deep Learning Techniques with a Case Study on Prognosticate Diagnostics of Liver Infection
S. Kowsalya and S. Saraswathi
Chapter 13 Case Study: Application of Ensemble Classifier for Diabetes Healthcare Data Analytics
P. Nagaraj, K. Muthamil Sudar, V. Muneeswaran, and Bhumika Choksi
Chapter 14 Deep Convolutional Neural Network Models for Early Detection of Breast Cancer from Digital Mammograms
A. Nithya and P. Shanmugavadivu
Chapter 15 Case Study: Deep Learning-Based Approach for Detection and Treatment of Retinopathy of Prematurity
S. Karkuzhali, K. Murugeswari, Thendral Puyalnithi, S. Senthilkumar, and G. Ganesan
Index
Biography
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.
