  Patient-provider communication has been crucial to cancer patients' survival
after their cancer treatments. However, the research community and patients
themselves often overlook the communication challenges after cancer treatments
as they are overshadowed by the severity of the patient's illness and the
variety and rarity of the cancer disease itself. Meanwhile, the recent
technical advances in AI, especially in Large Language Models (LLMs) with
versatile natural language interpretation and generation ability, demonstrate
great potential to support communication in complex real-world medical
situations. By interviewing six healthcare providers and eight cancer patients,
our goal is to explore the providers' and patients' communication barriers in
the post-cancer treatment recovery period, their expectations for future
communication technologies, and the potential of AI technologies in this
context. Our findings reveal several challenges in current patient-provider
communication, including the knowledge and timing gaps between cancer patients
and providers, their collaboration obstacles, and resource limitations.
Moreover, based on providers' and patients' needs and expectations, we
summarize a set of design implications for intelligent communication systems,
especially with the power of LLMs. Our work sheds light on the design of future
AI-powered systems for patient-provider communication under high-stake and
high-uncertainty situations.
