A fine-tuned large language model chatbot for multi-scenario radiology cancer care: randomized controlled trial on interaction optimization, emotional support, and provider burnout reduction

作者：Zhi Liu, Farrin Orouji, Fan Yang, Zhuowei Shi, Hongwei Liang, Bing Yu, Jianmin Wu, Zhipeng Wen, Long Tang, Hongyu Pan, Zhiwei Zhang, Yongmei Li, Liqiang Zhang · 发表于：Journal of Translational Medicine · 年份：2026 · DOI：10.1186/s12967-026-07738-6 · 研究领域：Artificial Intelligence in Healthcare and Education、AI in Service Interactions、Digital Mental Health Interventions

IMPORTANCE: Cancer patients are more prone to depression and anxiety symptoms compared to those with chronic diseases. Amidst surging clinical demands and constrained medical resources, the traditional radiology workflows, plagued by inefficient communication, exacerbates both patients' psychological distress and healthcare providers' burnout. OBJECTIVE: To develop and validate a fine-tuned DeepSeek R1-based Radiology Examination Chatbot (REC) to optimize clinical interaction between cancer patients and radiology healthcare providers (RHPs), thereby effectively providing emotional support for cancer patients and reducing burnout among RHPs. DESIGN, SETTING, AND PARTICIPANTS: Audio recordings of multi-scenarios (appointment triage (AT), pre-examination preparation (PP), radiology clinic services (RCS)) were collected from the radiology departments of three tertiary hospitals (n = 36,511 min). This study conducts two independent randomized controlled sub-trials for distinct patient groups: Sub-trial 1 evaluates AT/PP participants (1,424 patients, 1:1 randomized to RHP + REC or RHP), while Sub-trial 2 assesses RCS participants (638 patients, 1:1 randomized to the same groups). Due to differing patient populations, the sub-trials were designed and implemented separately. INTERVENTION: The REC was fine-tuned using domain-specific dialogue data (80% for training) and scenario-specific prompts, with GPT-o1 as a comparative benchmark. Sub-trials randomized patients to RHP + REC or RH...