图 书 馆
基于先验医学知识的电子医疗记录风险预测Risk Prediction on Electronic Healthcare Records with Prior Medical Knowledge |
|
| 课程网址: | http://videolectures.net/kdd2018_ma_risk_eletronic/ |
| 主讲教师: | Fenglong Ma |
| 开课单位: | 水牛城大学 |
| 开课时间: | 2018-11-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Predicting the risk of potential diseases from Electronic Health Records (EHR) has attracted considerable attention in recent years, especially with the development of deep learning techniques. Compared with traditional machine learning models, deep learning based approaches achieve superior performance on risk prediction task. However, none of existing work explicitly takes prior medical knowledge (such as the relationships between diseases and corresponding risk factors) into account. In medical domain, knowledge is usually represented by discrete and arbitrary rules. Thus, how to integrate such medical rules into existing risk prediction models to improve the performance is a challenge. To tackle this challenge, we propose a novel and general framework called PRIME for risk prediction task, which can successfully incorporate discrete prior medical knowledge into all of the state-of-the-art predictive models using posterior regularization technique. Different from traditional posterior regularization, we do not need to manually set a bound for each piece of prior medical knowledge when modeling desired distribution of the target disease on patients. Moreover, the proposed PRIME can automatically learn the importance of different prior knowledge with a log-linear model.Experimental results on three real medical datasets demonstrate the effectiveness of the proposed framework for the task of risk prediction |
| 关 键 词: | 电子健康记录; 机器学习模型; 风险预测 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2022-12-06：chenjy |
| 最后编审: | 2022-12-06：chenjy |
| 阅读次数: | 38 |