肺结节管理正由传统“单次影像判断”逐渐迈向“连续风险管理”模式，尤其在磨玻璃结节与微浸润性肺腺癌领 域，人工智能（AI）与医学 GPT 辅助决策的重要性日益显。本病例展示了1例经 BAIMGPT 肺结节智能体评估，成功纠正术后病理忽略的典型案例。患者为67岁女性，无吸烟史，但存在肝癌家族史，于2025年7月因左肺混合性结节至白教授AI门诊就诊。AI系统评估提示结节恶性概率高达88%，虽首次术后病理报告提示“无恶性肿瘤证据”，但经AI辅助病理复核与分子检测后，最终证实为微浸润性肺腺癌。该病例提示肺结节智能体不仅具有“发现病灶”能力，更正在进入“认知—推理—纠错—闭环 随访”的新阶段，对于减少早期肺癌漏诊具有重要临床价值。

The management of pulmonary nodules is gradually shifting from traditional "single image judgment" to "continuous risk management" mode, especially in the fields of ground glass nodules and microinvasive lung adenocarcinoma. The importance of artificial intelligence (AI) and medical GPT assisted decision-making is becoming increasingly prominent. This case presents a typical case where postoperative pathology was successfully corrected through BAIGPT pulmonary nodule intelligent agent evaluation. The patient is a 67 year old female with no smoking history. She visited Professor Bai's AI clinic in July 2025 due to mixed nodules in the left lung. The AI system evaluation showed that the probability of malignancy of the nodule was as high as 88%. Although the first postoperative pathological report indicated "no evidence of malignant tumor", after AI assisted pathological review and molecular testing, it was ultimately confirmed to be microinvasive lung adenocarcinoma. This case suggests that pulmonary nodule intelligent agents not only have the ability to "detect lesions", but are also entering a new stage of "cognition reasoning error correction closed-loop follow-up", which has important clinical value in reducing missed diagnosis of early lung cancer.