AI‐Driven Digital Twins for Simulating Physiotherapy Outcomes in Cancer Care

Implementing AI-supported digital twins (DTs) technology could help transform the personalization potential for physiotherapy practices in cancer care. This chapter attempts to synthesize the state of the art in AI-driven DTs in the rehabilitation of cancer patients. It analyzes the fundamentals of DT physiologic modeling that spans multiple scales, the contribution of AI as an autonomous agent and the infrastructure for movement simulation and therapy personalization. The chapter details specific use cases, such as shoulder rehabilitation after mastectomy, fatigue in cancer rehabilitation, gait training and pain management to demonstrate the wide range of uses. It discusses the potential for the rehabilitation of cancer patients through evidence from similar fields such as AR-based telerehabilitation, AI virtual clinics and musculoskeletal physiotherapy. Bibliometric analysis of recent publications indicates that in recent years, there has been a steep increase in DT studies in the rehabilitation field which signifies the increase in scholarly and clinical interest.