Deep Learning for Smart Healthcare
Trends, Challenges and Applications
- 308 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Deep Learning for Smart Healthcare
Trends, Challenges and Applications
About this book
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.
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Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Contents
- Preface
- List of Contributors
- 1 Deep Learning in Healthcare and Clinical Studies
- 2 Deep Learning Framework for Classification of Healthcare Data
- 3 Leveraging Deep Learning in Hate Speech Analysis on Social Platform
- 4 Medical Image Analysis Based on Deep Learning Approach for Early Diagnosis of Diseases
- 5 A Study of Medical Image Analysis using Deep Learning Approaches
- 6 Deep Learning for Designing Heuristic Methods for Healthcare Data Analytics
- 7 Deep Learning-Based Smart Healthcare System for Patient's Discomfort Detection
- 8 Gesture Identification for Hearing-Impaired through Deep Learning
- 9 Deep Learning-Based Cloud Computing Technique for Patient Data Management
- 10 Challenges and Issues in Health Care and Clinical Studies Using Deep Learning
- 11 Protecting Medical Images Using Deep Learning Fuzzy Extractor Model
- 12 Review of Various Deep Learning Techniques with a Case Study on Prognosticate Diagnostics of Liver Infection
- 13 Case Study: Application of Ensemble Classifier for Diabetes Healthcare Data Analytics
- 14 Deep Convolutional Neural Network Models for Early Detection of Breast Cancer from Digital Mammograms
- 15 Case Study: Deep Learning-Based Approach for Detection and Treatment of Retinopathy of Prematurity
- Index