Habit-based Behavior Change Medical Information Support System and Artificial Intelligence: Theories, Methods, and Data Analytics Approach provides a guideline to design and implement Habit-based Behavior Change Support Systems (HBCSS) which can change patient’s unhealthy habits to prevent the development of diseases. It presents theories, methods, management, and data analytics approach required to design, implement, and prescribe the use of HBCSS for several diseases’ management.It discusses topics such as theories of behavior change, ontologies and knowledge management, data mining, privacy and security, descriptive and prescription analytics. In addition, it discusses how to measure habit-change, future directions of the field, and case studies based on real-world examples.It is a valuable resource for clinicians, researchers, students, and member of the biomedical and medical fields who want to learn more about the use of medical systems to improve patients’ health.

• Discusses how habit-change features can be added to medical information systems to change patient’s unhealthy habits
• Describes the habit-change life cycle and framework so that readers can develop their own system
• Outlines how data analytics features are used to diagnose and predict unhealthy habits and prescribe changes to improve overall health of patients