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Multiturn Large Language Model-Based Conversational Agents for Patients With Cancer and Caregivers: Scoping Review
Yeongrok Jeong1, Hyejeon Cha2, Eunyoung E Suh1
1Center for World-leading Human-care Nurse Leaders for the Future by Brain Korea 21 (BK21) Four Project, College of Nursing, Research Institute of Nursing Science, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea, 82 027408807.
This review found only 8 studies on large language model (LLM)-based chatbots for cancer patients, highlighting early-stage development. Future research needs to focus on improving conversational abilities, safety, and transparent reporting for these AI health tools.
Area of Science:
- Artificial Intelligence in Oncology
- Digital Health Interventions
- Conversational Agent Technology
Background:
- Large language model (LLM)-based conversational agents are emerging in healthcare, but their ability for genuine multiturn dialogue is understudied.
- In oncology, these agents could address complex patient and caregiver needs for information, symptom consultation, and emotional support.
- Limited research exists on multiturn conversational agents specifically for cancer patients and informal caregivers.
Conclusions:
- The field of LLM-based multiturn chatbots for cancer care is nascent, with only 8 identified studies.
- Current research is characterized by prototype focus, diverse designs/evaluations, and inconsistent safety/transparency reporting.
- Future development must prioritize robust conversational capabilities, safety protocols, and transparent reporting practices.
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