摘要
利用深度强化学习方法预测分析老年肺癌发病高危人群的干预效果,生成按年龄和性别分组的干预效果预测模型。探索基于深度Q网络模型的预测分析方法,研究肺癌发病高危人群的干预效果和干预策略,构建干预对象、干预策略和干预效果之间的协同联动机制,可为肺癌预防干预和早诊早治提供新思路和实现积极应对人口老龄化的战略目标。
The prediction model of intervention effects was established according to the age and sex of elderly populations at high risk of lung cancer by analyzing the intervention effects with deep reinforcement learning method.The studies on prediction analysis methods,intervention effects and intervention strategies in elderly populations at high risk of lung cancer based on the deep Q network model by prediction analysis and establishment of synergistic coordination mechanism for intervention objects,intervention strategies and intervention effects can provide new ideas for the prevention,intervention,early diagnosis and treatment of lung cancer and can thus realize the strategic target for the aging populations.
作者
陈松景
吴思竹
CHEN Song-jing;WU Si-zhu(Institute of Medical Information,Chinese Academy of Medical Sciences/Beijing Union Medical College,Beijing 100020,China)
出处
《中华医学图书情报杂志》
CAS
2021年第8期15-19,共5页
Chinese Journal of Medical Library and Information Science
基金
教育部人文社会科学研究青年基金项目“基于深度学习的多源医学数据融合模式研究”(19YJC870002)
国家自然科学基金青年科学基金项目“基于深度强化学习的老年肺癌发病高危干预模式研究”(62106286)。
关键词
深度强化学习
干预效果
预测分析
肺癌
人口老龄化
Deep reinforcement learning
Intervention effect
Prediction analysis
Lung cancer
Aging population
