Identifying Clinical and Genomic Features Associated With Chronic Kidney Disease

被引：0

作者：

Moreno, M. Megan ^{[1
]}

Bain, Travaughn C. ^{[1
]}

Moreno, Melissa S. ^{[1
]}

Carroll, Katherine C. ^{[1
,2
,3
]}

Cunningham, Emily R. ^{[1
,2
,4
]}

Ashton, Zoe ^{[1
]}

Poteau, Roby ^{[1
]}

Subasi, Ersoy ^{[5
]}

Lipkowitz, Michael ^{[6
]}

Subasi, Munevver Mine ^{[1
]}

机构：

[1] Florida Inst Technol, Dept Math Sci, Melbourne, FL 32901 USA

[2] Dept Biomed & Chem Engn & Sci, Melbourne, FL USA

[3] Univ Florida, Dept Biol, Gainesville, FL USA

[4] SUNY Coll Potsdam, Dept Math, Potsdam, NY USA

[5] Florida Inst Technol, Dept Comp Engn & Sci, Melbourne, FL 32901 USA

[6] Georgetown Univ, Med Ctr, Dept Med, Washington, DC USA

来源：

FRONTIERS IN BIG DATA | 2021年 / 3卷

基金：

美国国家卫生研究院; 美国国家科学基金会;

关键词：

classification; genomic analysis; AASK; chronic kidney disease; decision trees; BLOOD-PRESSURE CONTROL; URINARY ALBUMIN EXCRETION; DIABETIC-NEPHROPATHY; AFRICAN-AMERICAN; RENAL OUTCOMES; PROGRESSION; INHIBITION; IRBESARTAN; DECLINE; BLACKS;

D O I：

10.3389/fdata.2020.528828

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We apply a pattern-based classification method to identify clinical and genomic features associated with the progression of Chronic Kidney disease (CKD). We analyze the African-American Study of Chronic Kidney disease with Hypertension dataset and construct a decision-tree classification model, consisting 15 combinatorial patterns of clinical features and single nucleotide polymorphisms (SNPs), seven of which are associated with slow progression and eight with rapid progression of renal disease among African-American Study of Chronic Kidney patients. We identify four clinical features and two SNPs that can accurately predict CKD progression. Clinical and genomic features identified in our experiments may be used in a future study to develop new therapeutic interventions for CKD patients.

引用

页数：9

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