Ebook: Artificial Intelligence of Health-Enabled Spaces

Artificial Intelligence of Health-Enabled Spaces (AIoH) has made a number of revolutionary advances in clinical studies that we are aware of. Among these advances, intelligent and medical services are gaining a great deal of interest. Nowadays, AI-powered technologies are not only used in saving lives, but also in our daily life activities in diagnosing, controlling, and even tracking of COVID-19 patients. These AI-powered solutions are expected to communicate with cellular networks smoothly in the next-generation networks (5G/6G and beyond) for more effective/critical medical applications. This will open the door for other interesting research areas. This book focuses on the development and analysis of Artificial Intelligence (AI) model applications across multiple disciplines. AI-based Deep Learning models, fuzzy and hybrid intelligent systems, and intrinsic explainable models are also presented in this book. Some of the fields considered in this smart health-oriented book include AI applications in electrical engineering, biomedical engineering, environmental engineering, computer engineering, education, cyber security, chemistry, pharmacy, molecular biology, and tourism.

This book is dedicated to addressing the major challenges in fighting diseases and psychological issues using AI. These challenges vary from cost and complexity to availability and accuracy. The aim of this book is hence to focus on both the design and implementation aspects of AI-based approaches in the proposed health-related solutions.

Machine Learning-based approaches are very useful in medical fields for identifying different kinds of illnesses and other medical problems that are difficult to diagnose. It includes cancers which can be difficult to identify at early stages, and also certain genetic factors. There are various examples such as IBM Watson Genomics which uses various methods based on cognitive computing using the genome, which is primarily based on gene sequencing, allowing a fast analysis. Computer Vision is a technique based on machine learning and Deep Learning that is useful in diagnosing diseases using medical imaging. Computer Vision is helpful in segmenting and classifying medical images. Medical images are analysed accurately with the help of computer vision. As Machine Learning techniques are growing, IoT- enabled gadgets are being used for diagnosing medical issues through proper analysis of these medical images.

Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via intelligent enabling technologies.