This white paper on AI and ML as enablers of beyond 5G (B5G) networks is based on contributions from almost 20 5G PPP projects, coordinated through the 5G PPP Technology Board, that research, implement and validate 5G and B5G network systems. The paper introduces the main relevant mechanisms in Artificial Intelligence (AI) and Machine Learning (ML), currently investigated and exploited for enhancing 5G and B5G networks.

The holy grail in endoscopy examinations has for a long time been assisted diagnosis using Artificial Intelligence (AI). Recent developments in computer hardware are now enabling technology to equip clinicians with promising tools for computer-assisted diagnosis (CAD) systems. However, creating viable models or architectures, training them, and assessing their ability to diagnose at a human level, are complicated tasks. This is currently an active area of research, and many promising methods have been proposed. In this chapter, we give an overview of the topic. This includes a description of current medical challenges followed by a description of the most commonly used methods in the field. We also present example results from research targeting some of these challenges, and a discussion on open issues and ongoing work is provided. Hopefully, this will inspire and enable readers to future develop CAD systems for gastroenterology.

This book constitutes the refereed proceedings of the 15th International Conference on Cognitive Radio-Oriented Wireless Networks, CROWNCOM 2020, held in Rome, Italy, in November 2020. Due to COVID-19 pandemic the conference was held virtually.
The 13 revised full papers were selected from 28 submissions and present all major technical aspects related to cognitive radio and networks. The papers are organized in four sessions: spectrum sensing and environment awareness; resource sharing and optimization; verticals and applications; business models and spectrum management.