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[1]熊浩邓维姝.基于DeepSeek的智能减重管理系统设计与应用[J].中国卫生质量管理,2025,32(08):77-82.[doi:10.13912/j.cnki.chqm.2025.32.8.16]
　XIONG Hao,DENG Weishu.Design and Application of an Intelligent Weight-Loss Management System Based on DeepSeek[J].Chinese Health Quality Management,2025,32(08):77-82.[doi:10.13912/j.cnki.chqm.2025.32.8.16]

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基于DeepSeek的智能减重管理系统设计与应用

《中国卫生质量管理》[ISSN:1006-7515/CN:CN 61-1283/R] 卷: 32 期数: 2025年08期页码: 77-82 栏目: 质量与信息化出版日期: 2025-08-15

Title:: Design and Application of an Intelligent Weight-Loss Management System Based on DeepSeek

作者:: 熊浩邓维姝; 武汉大学中南医院

Author(s):: XIONG Hao; DENG Weishu; Zhongnan Hospital of Wuhan University

关键词:: DeepSeek; 医疗大模型; 精准筛查; 人工智能; 减重管理

Keywords:: DeepSeek; Large Medical Model; Precise Screening; Artificial Intelligence; Weight-Loss Management

分类号:: R197.324

DOI:: 10.13912/j.cnki.chqm.2025.32.8.16

文献标志码:: B

摘要:: 目的实现标准化智能减重管理，精准减重并降低慢病风险。方法根据医院减重业务流程和需求调研分析，开发了一款基于DeepSeek-R1大模型的智能减重管理系统。结果该系统试运行12周，共管理79例肥胖患者，平均减重4.4 kg，体脂率平均下降3.5%，系统共登录15 263次，完成记录4 266条，体重变化预测误差小于1 kg，自主选择健康饮食率达70%，运动目标完成率达63%，体重管理可持续性较好。结论智能减重管理系统有助于提升患者就医依从性，减轻临床工作负担，推动医疗智能化发展。

Abstract:: ObjectiveTo achieve standardized and intelligent weight-loss management, facilitate precise weight-loss, and reduce the risk of chronic diseases.MethodsBased on the investigation and analysis of the hospital’s weight-loss business processes and requirements, an intelligent weight-loss management system was developed using the DeepSeek-R1 large model.ResultsDuring a 12-week trial period, the system managed 79 obese patients, achieving an average weight loss of 4.4 kg and an average reduction in body fat percentage of 3.5%. The system was logged into 15 263 times, with 4 266 records completed. The prediction error for weight change was less than 1 kg. The rate of patients autonomously choosing healthy diets reached 70%, and the completion rate of exercise goals was 63%, indicating a certain improvement in the sustainability of weight management. Conclusion The intelligent weight-loss system contributes to enhancing patient compliance with medical advice, alleviating the clinical workload, and promoting the development of intelligent healthcare.

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更新日期/Last Update: 2025-08-15