图 书 馆
连续时间隐藏马尔可夫模型的疾病相互作用的可视化与预测Visualization and Prediction of Disease Interactions with Continuous-Time Hidden Markov Models |
|
| 课程网址: | http://videolectures.net/nipsworkshops2011_leiva_murillo_disease/ |
| 主讲教师: | Jose M. Leiva-Murillo |
| 开课单位: | 马德里卡洛斯三世大学 |
| 开课时间: | 2012-01-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | This paper describes a method for discovering disease relationships and the evolution of diseases from medical records. The method makes use of continuous-time Markov chain models that overcome some drawbacks of the more widely used discrete-time chain models. The model addresses uncertainty in the diagnoses, possible diagnosis errors and the existence of multiple alternative diagnoses in the records. A set of experiments, performed on a dataset of psychiatric medical records, shows the capability of the model to visualize maps of comorbidity and causal interactions among diseases as well as to perform predictions of future evolution of diseases. |
| 关 键 词: | 计算机科学; 机器学习; 马尔可夫过程 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-11-13：yumf |
| 阅读次数: | 31 |