Artificial intelligence (AI) systems for interpreting complex medical datasets

被引：46
|
作者：
Altman, R. B. [1 ]
机构：
[1] Stanford Univ, Stanford, CA 94305 USA
来源：
CLINICAL PHARMACOLOGY & THERAPEUTICS | 2017年 / 101卷 / 05期
关键词：
D O I：
10.1002/cpt.650
中图分类号：
R9 [药学];
学科分类号：
1007 ;
摘要：
Advances in machine intelligence have created powerful capabilities in algorithms that find hidden patterns in data, classify objects based on their measured characteristics, and associate similar patients/diseases/drugs based on common features. However, artificial intelligence (AI) applications in medical data have several technical challenges: complex and heterogeneous datasets, noisy medical datasets, and explaining their output to users. There are also social challenges related to intellectual property, data provenance, regulatory issues, economics, and liability.
引用
收藏
页码：585 / 586
页数：2
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