With the development of society and the changes in people's lifestyles, more chronic illnesses have become the world’s biggest killers. According to the World Health Organization (WHO), ischemic heart disease, stroke, chronic obstructive lung disease, and lower respiratory infections have remained the top killers during the past decade in both developed and developing countries. Artificial intelligence (AI) has emerged as a promising technology in healthcare with many applications, including diagnosis, treatment, prevention, and medical payment systems. Recently, a great number of new information technologies have emerged to assist the applications of AI in healthcare, such as big data and mobile internet networks. Therefore, AI-based electronic (E)-healthcare and medical (M)-healthcare solutions are aimed at gaining information, processing it, and giving a well-defined output to the end-user (the physician, the patient, or the caregiver).

AI-based E-healthcare and M-healthcare have shown significant potential to achieve the goals and demands of medical treatment. Owing to the data-driven approach, AI has brought a paradigm shift from information fields to other applications, such as intelligent diagnosis and treatment, intelligent payment, intelligent drug research and development, Intelligent Health Management and Diagnosis Related Groups, etc. Consequently, many researchers in the information and communication technology field are focusing on AI for healthcare applications.

This is Special Issue aims to bring together researchers to report recent research in AI in healthcare and exchange new ideas with innovative technologies and solutions towards AI in E-healthcare and M-healthcare applications. In view of the current strong interest in AI in E-health-care and M-healthcare, we invite researchers to contribute to original research and review articles to identify opportunities for AI in E-health-care and M-healthcare and to address the challenges that this brings.

Potential topics include but are not limited to the following:

• AI-driven diagnosis related groups for E-health-care and M-healthcare
• AI-driven chronic disease analysis, such as stroke, hypertension, cancer, coronary heart disease, diabetes, and chronic respiratory disease
• AI-driven remote treatment for E-health-care and M-healthcare
• AI-driven medical payment systems
• AI-driven physical layer technologies of E-health-care and M-healthcare
• AI-driven multiple access layer technologies of E-health-care and M-healthcare
• AI-driven network layer technologies of E-health-care and M-healthcare