Construction of an intelligent prediction system for recurrence of patients with differentiated thyroid carcinoma after endoscopic surgery
Objective To construct and verify an intelligent prediction system for recurrence of patients with differentiated thyroid cancer(DTC)after endoscopic surgery based on depth algorithm.Methods The clinical data of 189 patients with DTC who underwent endoscopic surgery at Shangluo Central Hospital from October 2020 to October 2023 were retrospectively analyzed,and were divided into a training set(126 cases)and a validation set(63 cases)by simple random sampling according to the ratio of 2:1.In the training set,there were 39 males and 87 females who were(49.14±7.78)years old.In the verification set,there were 22 males and 41 females who were(50.38±8.12)years old.The patients in the training set were divided into a recurrence group(24 cases)and a non-recurrence group(102 cases)according to whether they had recurred or not.The Cox regression analysis was used to explore the factors affecting the patients'recurrence.Based on the obtained influencing factors,the convolutional neural network(CNN)depth algorithm was used to construct an intelligent prediction system for the patients'recurrence.The receiver operating characteristic curve(ROC)was used to evaluate the predictive efficacy of the intelligent prediction system.t and x2 tests were applied.Results The postoperative recurrence rate of the patients undergoing endoscopic treatment was 18.52％(35/189).Maximum tumor diameter ≥2 cm[hazard ratio(HR)=1.660,95％confidence interval(95％CI)1.169-2.358],moderate differentiation(HR=1.484,95％CI 1.081-2.039),lymph node metastasis(HR=1.876,95％CI 1.258-2.798),subtotal thyroidectomy(HR=1.800,95％CI 1.238-2.618),no adjuvant therapy(HR=1.737,95％CI 1.213-2.486),and serum thyroid globulin antibody(TgAb)≥40 IU/ml(HR=1.590,95％CI 1.126-2.246)were risk factors for the patients'recurrence(all P＜0.05).The accuracy of the DTC endoscopic postoperative recurrence intelligent prediction system based on CNN dept algorithm was 0.85;the recall rate was 0.88;the F1 value was 0.88.The ROC analysis results showed that the areas under the curves(AUC)of the training set and the validation set of the DTC postoperative recurrence intelligent prediction system constructed based on CNN were 0.901(95％CI 0.835-0.947)and 0.872(95％CI 0.763-0.943).Conclusion The intelligent prediction system for recurrence of patients with DTC after endoscopic surgery based on depth algorithm has good prediction efficacy,and has good application value in the prediction of recurrence of patients with DTC after endoscopic surgery.
万方数据
维普
