The book aims to provide a deeper understanding of the synergistic impact of Artificial intelligence (AI) and the Internet of Things (IoT) for disease detection. It presents a collection of topics designed to explain methods to detect different diseases in humans and plants. Chapters are edited by experts in IT and machine learning, and are structured to make the volume accessible to a wide range of readers.

Key Features:

- 17 Chapters present information about the applications of AI and IoT in clinical medicine and plant biology

- Provides examples of algorithms for heart diseases, Alzheimer’s disease, cancer, pneumonia and more

- Includes techniques to detect plant disease

- Includes information about the application of machine learning in specific imaging modalities

- Highlights the use of a variety of advanced Deep learning techniques like Mask R-CNN

- Each chapter provides an introduction and literature review and the relevant protocols to follow

The book is an informative guide for data and computer scientists working to improve disease detection techniques in medical and life sciences research. It also serves as a reference for engineers working in the healthcare delivery sector.