Machine Learning and Other Emerging Decision Support Tools

被引：8

作者：

Baron, Jason M. ^{[1
]}

Kurant, Danielle E. ^{[1
]}

Dighe, Anand S. ^{[1
]}

机构：

[1] Harvard Med Sch, Massachusetts Gen Hosp, Dept Pathol, 55 Fruit St, Boston, MA 02214 USA

来源：

CLINICS IN LABORATORY MEDICINE | 2019年 / 39卷 / 02期

关键词：

Machine learning; Clinical decision support; Artificial intelligence; Knowledge discovery; Computational pathology; IMPUTATION; ETHICS;

D O I：

10.1016/j.cll.2019.01.010

中图分类号：

R446 [实验室诊断]; R-33 [实验医学、医学实验];

学科分类号：

1001 ;

摘要：

Emerging applications of machine learning and artificial intelligence offer the opportunity to discover new clinical knowledge through secondary exploration of existing patient medical records. This new knowledge may in turn offer a foundation to build new types of clinical decision support (CDS) that provide patient-specific insights and guidance across a wide range of clinical questions and settings. This article will provide an overview of these emerging approaches to CDS, discussing both existing technologies as well as challenges that health systems and informaticists will need to address to allow these emerging approaches to reach their full potential.

引用

页码：319 / +

页数：14

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