Artificial Intelligence for Predicting and Diagnosing Complications of Diabetes

被引:17
|
作者
Huang, Jingtong [1 ]
Yeung, Andrea M. M. [1 ]
Armstrong, David G. G. [2 ]
Battarbee, Ashley N. N. [3 ]
Cuadros, Jorge [4 ]
Espinoza, Juan C. C. [5 ]
Kleinberg, Samantha [6 ]
Mathioudakis, Nestoras [7 ]
Swerdlow, Mark A. A. [2 ]
Klonoff, David C. C. [1 ,8 ]
机构
[1] Diabet Technol Soc, Burlingame, CA USA
[2] Univ Southern Calif, Keck Sch Med, Los Angeles, CA USA
[3] Univ Alabama Birmingham, Ctr Womens Reprod Hlth, Birmingham, AL USA
[4] Univ Calif Berkeley, Meredith Morgan Optometr Eye Ctr, Berkeley, CA USA
[5] Univ Southern Calif, Childrens Hosp Los Angeles, Los Angeles, CA USA
[6] Stevens Inst Technol, Hoboken, NJ USA
[7] Johns Hopkins Univ, Baltimore, MD USA
[8] Diabet Res Inst, Mills Peninsula Med Ctr, 100 South San Mateo Dr,Room 5147, San Mateo, CA 94401 USA
来源
关键词
diabetes; complications; artificial intelligence; machine learning algorithm; risk factors; prediction; KIDNEY-DISEASE; INPATIENT HYPOGLYCEMIA; PERIPHERAL NEUROPATHY; VALIDATION; RISK; MODEL; NEPHROPATHY;
D O I
10.1177/19322968221124583
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Artificial intelligence can use real-world data to create models capable of making predictions and medical diagnosis for diabetes and its complications. The aim of this commentary article is to provide a general perspective and present recent advances on how artificial intelligence can be applied to improve the prediction and diagnosis of six significant complications of diabetes including (1) gestational diabetes, (2) hypoglycemia in the hospital, (3) diabetic retinopathy, (4) diabetic foot ulcers, (5) diabetic peripheral neuropathy, and (6) diabetic nephropathy.
引用
收藏
页码:224 / 238
页数:15
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