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目的:观察精准营养治疗对2型糖尿病（T2DM）患者膳食模式和食欲的调节作用。方法:采用便利抽样法，选取2018年9月—2019年9月于新疆医科大学第一附属医院内分泌科经治疗后出院的T2DM患者155例，随机分为对照组73例和试验组82例。对照组接受常规的营养干预，试验组在常规随访干预的基础上，基于医学人工智能系统建立患者个体化数据模型进行精准化的营养治疗，主要包括建立糖尿病饮食管理处方和智能化饮食干预。采用膳食模式调查问卷和简化营养食欲调查问卷（SNAQ）比较两组干预前后膳食模式和食欲的变化。结果:干预3个月后，两组蛋白质、脂肪、碳水化合物摄入合理的患者比例均较干预前提高，且试验组高于对照组，差异有统计学意义（n P<0.05）。干预3个月后，试验组SNAQ问卷得分（13.20±1.54）分，对照组（10.32±1.25）分，差异有统计学意义（n t=-12.838，n P<0.05）。n 结论:基于医学人工智能系统建立大数据模型进行精准化的营养治疗可以更好地规范T2DM患者的膳食行为，提高患者食欲。“,”Objective:To explore the effect of precision nutrition therapy on the dietary pattern and appetite of patients with type 2 diabetes mellitus (T2DM) .Methods:From September 2018 to September 2019, convenience sampling method was used to select 155 patients with T2DM discharged from the Endocrinology Department of the First Affiliated Hospital of Xinjiang Medical University. All patients were randomly divided into control group (73 cases) and experimental group (82 cases) . Control group received routine nutritional intervention. Based on routine follow-up intervention, experimental group established a patient's personalized data model according to the medical artificial intelligence system for precise nutritional treatment, including the establishment of diabetes diet management prescriptions and intelligent diet intervention. The Dietary Pattern Questionnaire and the Simplified Nutritional Appetite Questionnaire (SNAQ) were used to compare the changes in dietary patterns and appetite before and after intervention between two groups.Results:After three months of intervention, the proportion of patients with reasonable protein, fat, and carbohydrate intake in two groups was higher than that before intervention, and that of experimental group was higher than that of control group, and the difference was statistically significant (n P<0.05) . After three months of intervention, the score of SNAQ of experimental group and control group was (13.20±1.54) and (10.32±1.25) respectively, and the difference was statistically significant (n t=-12.838, n P<0.05) .n Conclusions:The establishment of a big data model based on a medical artificial intelligence system for precise nutritional therapy can regulate the dietary behavior of patients with T2DM and increase their appetite.