多层感知器
变量(数学)
癌症
灵敏度(控制系统)
人工智能
癌症复发
机器学习
医学
计算机科学
人工神经网络
数学
内科学
工程类
数学分析
电子工程
作者
Yongkang Cai,Yutong Xie,Shulian Zhang,Yuepeng Wang,Yan Wang,Jian Chen,Zhiquan Huang
出处
期刊:Head & neck
[Wiley]
日期:2023-10-03
卷期号:45 (12): 3053-3066
摘要
Postoperative recurrence of oral cancer is an important factor affecting the prognosis of patients. Artificial intelligence is used to establish a machine learning model to predict the risk of postoperative recurrence of oral cancer.The information of 387 patients with postoperative oral cancer were collected to establish the multilayer perceptron (MLP) model. The comprehensive variable model was compared with the characteristic variable model, and the MLP model was compared with other models to evaluate the sensitivity of different models in the prediction of postoperative recurrence of oral cancer.The overall performance of the MLP model under comprehensive variable input was the best.The MLP model has good sensitivity to predict postoperative recurrence of oral cancer, and the predictive model with variable input training is better than that with characteristic variable input.
科研通智能强力驱动
Strongly Powered by AbleSci AI