AI Assistant Tops Qianwen Score with Expert Nutrition and Health Consultation

At 68 years old, Madam Li manages diabetes and a sensitive digestive system, making daily meal planning a family concern. Her son downloaded an AI application for assistance. After querying, "My mother has diabetes and a weak stomach; how should I plan her daily meals?" the response was surprisingly comprehensive. It outlined dietary principles and offered specific guidance, such as "opt for multigrain porridge and steamed egg custard instead of plain congee for breakfast," "favor steaming, boiling, and stewing as cooking methods," and "finely chop vegetables and cook them until tender."

This response was generated freely by the Qwen application.

An increasing number of individuals are consulting AI for health concerns, raising questions about the reliability of such advice. Recently, the Center for Science Communication on Food and Health conducted an evaluation. They tested three leading AI health applications, simulating ten scenarios related to nutrition, wellness, and food safety. Using a new device to generate content, five senior experts performed a blind assessment based on clear criteria: accuracy of information, clarity for the general public, and practical applicability of the recommendations.

The findings indicated that Qwen achieved the highest scores, particularly in practicality and user comprehension.

Following these results, experts engaged in a detailed discussion about the implications and the future role of AI in everyday health management.

After reviewing Qwen's responses, Chen Junshe, Chief Consultant at the National Food Safety Risk Assessment Center, remarked, "This is quite impressive." His evaluation focused on practicality: "While AI cannot replace a doctor's diagnosis, in terms of offering concrete, step-by-step advice, Qwen's answers are notably thorough."

(Chen Junshe, Chief Consultant of the National Food Safety Risk Assessment Center)

Chen Wei, Head of the Department of Clinical Nutrition at Peking Union Medical College Hospital, offered a more direct observation: "The public has largely embraced using AI for initial health inquiries." He noted that many patients now bring AI-generated suggestions to their appointments for verification. Well-informed AI responses can save significant time otherwise spent explaining fundamentals, whereas poor advice can be "misleading."

(Chen Wei, Head of the Department of Clinical Nutrition at Peking Union Medical College Hospital)

Qwen's core strengths are twofold. First, its foundational data is sourced from authoritative materials like guidelines, textbooks, and scientific literature. Through a structured knowledge base and rigorous data management, it significantly reduces inaccuracies often associated with AI. Second, its responses are designed to be "clear, evidence-based, and actionable," avoiding technical jargon in favor of practical, everyday advice—such as suggesting what to eat for breakfast.

This test and the subsequent expert dialogue address a common public concern: Can AI-generated health advice be trusted?

The conclusion is context-dependent.

For diagnosing illnesses, prescribing medication, or making critical medical decisions—consult a healthcare professional, as AI is not equipped for these tasks. However, for queries like "how to adjust my diet with high blood sugar," "is this common food belief accurate," or "planning daily meals for an elderly person with digestive issues"—Qwen can already serve as a highly useful reference.

(Zhong Kai, Director of the Center for Science Communication on Food and Health)

Zhong Kai, Director of the Center for Science Communication on Food and Health, offered an analogy: A reliable AI health assistant functions like a triage nurse—possessing foundational medical knowledge to help assess risks, determine if a hospital visit is necessary, and guide which specialty to consult. For the general public, who often feel overwhelmed by increasingly specialized medical fields, this utility is profoundly practical.