基于舌象特征逻辑回归的肺癌风险预警模型研究OACSTPCD
Study on Lung Cancer Risk Warning Model Based on Tongue Image Feature Logistic Regression
目的 分析良恶性肺结节的客观化舌诊数据特征,并基于逻辑回归方法建立肺癌风险预警模型.方法 选取2020年7月-2022年3月上海中医药大学附属龙华医院肿瘤科263例肺癌患者(肺癌组),上海中医药大学附属曙光医院体检中心292例良性肺结节患者(良性肺结节组)和307例健康体检者(健康对照组),使用TFDA-1型数字舌面诊仪采集3组受试者的舌象图像,通过特征提取技术获取舌象客观诊断特征,分析3组受试者舌象指标分布特征,通过特征筛选后基于逻辑回归方法建立肺癌预警模型,并使用敏感性、特异性、准确率及受试者工作特征(ROC)曲线下面积(AUC)评估模型性能.结果 良性肺结节组舌象特征与健康对照组相近;肺癌组与健康对照组、肺癌组与良性肺结节组舌象特征差异较大,肺癌患者舌象偏晦黯、舌质偏红、舌苔偏薄黄腻.基于舌象数据的肺癌预警模型准确率为70.09%、敏感性为69.94%、特异性为70.29%、AUC为0.769.在舌象数据集基础上加入基线信息后重新建模,模型诊断效能提升,基于基线信息与舌象数据的新模型准确率为77.30%、敏感性为75.94%、特异性为79.15%、AUC为0.812.结论 良性肺结节患者与肺癌患者客观舌象数据统计特征存在显著差异,基于舌象客观数据的肺癌分类模型表现良好,中医客观舌诊数据可为良性肺结节和肺癌的鉴别诊断提供参考.
Objective To analyze the objective tongue diagnosis data characteristics of benign and malignant pulmonary nodules and to establish a lung cancer risk warning model based on the logistic regression method.Methods From July 2020 to March 2022,263 lung cancer patients(lung cancer group)from the Oncology Department of Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine,292 benign pulmonary nodules patients(benign pulmonary nodules group)from the Physical Examination Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine,and 307 healthy individuals(healthy control group)were selected.TFDA-1 digital tongue diagnostic instrument was used to collect tongue images.Objective diagnostic features of the tongue were obtained through feature extraction technology.The distribution characteristics of the tongue indicators of the three groups of subjects were analyzed.A lung cancer warning model was established based on logistic regression method after feature screening,and the performance of the model was evaluated using sensitivity,specificity,accuracy,and AUC.Results The tongue features of patients in benign pulmonary nodules group were similar to those of the healthy control group,while the tongue features of the lung cancer group differed greatly from those of the healthy control group and benign pulmonary nodules group.The tongue features of lung cancer patients were dark and opaque,the tongue body was reddish,and the tongue coating is thin and yellowish with a greasy texture.The accuracy,sensitivity,specificity and AUC of the lung cancer warning model based on tongue image data were 70.09%,69.94%,70.29%and 0.769,respectively.After adding baseline information to the tongue image data set,the models'performance was improved.The accuracy,sensitivity,specificity and AUC of the new model based on tongue and baseline were 77.30%,75.94%,79.15%and 0.812,respectively.Conclusion The statistical characteristics of objective tongue image data between benign pulmonary nodules and lung cancer patients show significant differences.The lung cancer classification model based on objective tongue data performs well,and the objective tongue diagnosis data in TCM can provide reference for the differential diagnosis of benign pulmonary nodules and lung cancer.
石玉琳;春意;刘嘉懿;刘苓霜;许家佗
上海中医药大学教务处,上海 201203上海中医药大学中医学院,上海 201203上海中医药大学附属龙华医院,上海 200032
中医学
肺结节肺癌舌诊逻辑回归风险预警模型
benign pulmonary nodulelung cancertongue imagelogistic regressionrisk warning model
《中国中医药信息杂志》 2024 (010)
149-156 / 8
上海市"科技创新行动计划"启明星培育(扬帆专项)(22YF1448900);国家自然科学基金青年科学基金(82305090);上海市卫健委临床研究专项(20234Y0168);国家重点研发计划-中医药现代化研究重点专项(2017YFC1703301)
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