肥胖/超重已成为累及多系统的复杂代谢性疾病，传统依赖门诊随访与短期减重的模式难以解决预测不足、干预 粗放、依从性差和资源不均等问题。近年来，人工智能（AI/ML）、大语言模型（LLM/GPT）、物联网（IoT）、元宇宙和数字人被引入体重管理全链条：在预防阶段，多模态风险模型与可穿戴设备实现高危人群早期识别和行为预警，元宇宙场景提升健康教育与参与度；在诊断阶段，AI 支持肥胖表型重构、体成分自动分析及并发症“红灯信号”识别，推动体重控制从“以 BMI 为中心”转向 “以表型与并发症为中心”；在治疗与康复阶段，AI 辅助GLP-1等减重药物精准获益预测、数字疗法与行为教练个体化推送、 代谢手术的全流程风险评估，并通过VR/GDTx与数字孪生促进功能恢复与防复胖。管理层面，形成以云—边—端架构为基础、嵌入5P医学理念的综合平台，医学GPT/BAIMGPT作为“减重数字人专家”连接医生、患者与管理者。当前主要挑战包括数据质量与泛化性、公平性与隐私保护、临床流程与支付模式适配以及 GPT 安全监管。展望未来，AI与数字孪生、元宇宙深度融合，有望实现从单纯“减重”走向“代谢健康与自我管理能力”的系统性提升。

Obesity/overweight has become a complex metabolic disease involving multiple systems, and the traditional model  of relying on outpatient follow-up and short-term weight loss is difficult to solve the problems of insufficient prediction, extensive  intervention, poor adherence and unequal resources. In recent years, artificial intelligence (AI/ML), large language models (LLM/GPT), Internet of Things (IoT), metaverse and digital humans have been introduced into the whole chain of weight management: in the prevention stage, multimodal risk models and wearable devices achieve early identification and behavior warning of high-risk groups, and metaverse scenarios improve health education and participation; In the diagnostic stage, AI supports obesity phenotype reconstruction, automatic body composition analysis, and complication “red light signal” recognition, promoting weight control from“BMI-centric”to “phenotype and complication-centric”; In the treatment and rehabilitation stage, AI-assisted accurate benefit  prediction of weight loss drugs such as GLP-1, personalized push of digital therapy and behavioral coaching, full-process risk  assessment of metabolic surgery, and promotion of functional recovery and anti-obesity through VR/GDTx and digital twins. At the  management level, a comprehensive platform based on cloud-edge-end architecture and embedded with 5P medical concepts has been  formed, and medical GPT/BAIMGPT connects doctors, patients and managers as a “weight loss digital human expert”. The main  challenges include data quality and generalization, fairness and privacy protection, clinical process and payment model adaptation, and  GPT security regulation. Looking forward to the future, the deep integration of AI, digital twins, and the metaverse is expected to  achieve systematic improvement from simple “weight loss” to “metabolic health and self-management ability”.