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Developing a Quality Evaluation Index System for Health Conversational Artificial Intelligence: Mixed Methods Study

Developing a Quality Evaluation Index System for Health Conversational Artificial Intelligence: Mixed Methods Study

Wang et al [62] also noted that LLMs may not achieve complete deidentification of training data, thereby raising the risk of exposing sensitive user information. Within the health consultation capability dimension, the highest weight was assigned to “treatment recommendation generation ability” (0.2019). Among its tertiary indicators, “accuracy of treatment recommendations” (0.1216) and “comprehensiveness of treatment recommendations” (0.0562) were assigned relatively high weights.

Weizhen Liao, Meng Li, Chengyu Ma, Youli Han, Dan Wang, Haopeng Liu, Yi Wang, Zijie Feng, Huichao Wang, Yiru Guan

J Med Internet Res 2026;28:e83188