Foundations of Causal ML

Health Informatics Artificial Intelligence and Machine Learning in Health Care and Medical Sciences(2024)

引用 0|浏览1
摘要
AbstractThe present chapter covers the important dimension of causality in ML both in terms of causal structure discovery and causal inference. The vast majority of biomedical ML focuses on predictive modeling and does not address causal methods, their requirements and properties. Yet these are essential for determining and assisting patient-level or healthcare-level interventions toward improving a set of outcomes of interest. Moreover causal ML techniques can be instrumental for health science discovery.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
0
您的评分 :

暂无评分

数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn