ABSTRACT

This handbook provides thorough, in-depth, and well-focused developments of artificial intelligence (AI), machine learning (ML), deep learning (DL), natural language processing (NLP), cryptography, and blockchain approaches, along with their applications focused on healthcare systems.

Handbook of AI-Based Models in Healthcare and Medicine: Approaches, Theories, and Applications highlights different approaches, theories, and applications of intelligent systems from a practical as well as a theoretical view of the healthcare domain. It uses a medically oriented approach in its discussions of human biology, healthcare, and medicine and presents NLP-based medical reports and medicine enhancements. The handbook includes advanced models of ML and DL for the management of healthcare systems and also discusses blockchain-based healthcare management. In addition, the handbook offers use cases where AI, ML, and DL can help solve healthcare complications.

Undergraduate and postgraduate students, academicians, researchers, and industry professionals who have an interest in understanding the applications of ML/DL in the healthcare setting will want this reference on their bookshelf.

chapter 1|18 pages

Edge Computing in Healthcare

Concepts, Tools, Techniques, and Use Cases

chapter 5|23 pages

3D Volumetric Computed Tomography from 2D X-Rays

A Deep Learning Perspective

chapter 10|17 pages

RetinalAlexU-Net

Segmentation of the Retinal Vascular Network for the Diagnosis of Diabetic Retinopathy

chapter 14|28 pages

Heartcare Assistance System

A Machine Learning-Based Cardiovascular Risk Monitoring Tool (CRMT)

chapter 18|31 pages

Digital Histopathology

Paving Future Directions Towards Predicting Diagnosis of Disease Via Image Analysis

chapter 22|14 pages

Autism, ADHD and Dyslexia Disorder Comorbidity

An Enhanced Study on Education for Children through Artificial Intelligence-Enabled Personalized Assistive Tools