Department of Ultrasound, The Affiliated Changzhou No. 2 People's Hospital with Nanjing Medical University, Changzhou 213004, China.
Graduate School, Dalian Medical University, Dalian 116000, China.
J Healthc Eng. 2022 Feb 8;2022:1872412. doi: 10.1155/2022/1872412. eCollection 2022.
In this paper, we mainly adopted 337 patients who had undergone the surgery on lymph node metastasis of papillary thyroid carcinoma (PTC) as the sample population. In order to provide clinical reference for the intelligent decision-making in treatment plan and improvement of prognosis, we utilized ultrasound features and imaging features to construct five early diagnosis models for patients based on the ultrasound features, imaging features, and combined features. The model integrated with broad learning system (BLS) showed the best performance, with the area under the curve (AUC) of 0.857 (95% confidence interval (CI): 0.811-0.902)) and the accuracy of 0.805 (95% CI: 0.759-0.850). For demographic and clinical features, the prediction effect was also good, with the AUC more than 0.700.
本文主要选取了 337 例行颈淋巴结转移癌清扫术的甲状腺乳头状癌(PTC)患者作为样本人群。为了为治疗方案的智能决策和预后的改善提供临床参考,利用超声特征和影像学特征,基于超声特征、影像学特征和联合特征构建了 5 种患者的早期诊断模型。综合了广义回归神经网络(BLS)的模型表现最佳,曲线下面积(AUC)为 0.857(95%置信区间(CI):0.811-0.902)),准确率为 0.805(95%CI:0.759-0.850)。对于人口统计学和临床特征,预测效果也较好,AUC 均大于 0.700。