Letter to the Editor Regarding "Predicting Asthma Exacerbations Using Machine Learning Models"

被引：0

作者：

Yu, Zekai ^{[1
]}

机构：

[1] Hangzhou Dianzi Univ, 1158,2 Rd,Xiasha Higher Educ Zone, Hangzhou 310018, Zhejiang, Peoples R China

来源：

ADVANCES IN THERAPY | 2025年 / 42卷 / 05期

关键词：

Asthma; Electronic health records; Exacerbations; Machine learning; Physician diagnosed asthma; Real-world prediction; XGBoost;

D O I：

10.1007/s12325-025-03119-5

中图分类号：

R-3 [医学研究方法]; R3 [基础医学];

学科分类号：

1001 ;

摘要：

引用

页码：2537 / 2538

页数：2

共 5 条

[1] Predicting Effective Thermal Conductivity of Sintered Silver by Microstructural-Simulation-Based Machine Learning [J].

Du, Chengjie ;

Zou, Guisheng ;

Feng, Bin ;

Huo, Jinpeng ;

Zhanwen, A. ;

Xiao, Yu ;

Wang, Wengan ;

Liu, Lei .

JOURNAL OF ELECTRONIC MATERIALS, 2023, 52 (04) :2347-2358

[2] Determining asthma endotypes and outcomes: Complementing existing clinical practice with modern machine learning [J].

Ray, Anuradha ;

Das, Jishnu ;

Wenzel, Sally E. .

CELL REPORTS MEDICINE, 2022, 3 (12)

[3] Genetics of chronic respiratory disease [J].

Sayers, Ian ;

John, Catherine ;

Chen, Jing ;

Hall, Ian P. .

NATURE REVIEWS GENETICS, 2024, 25 (08) :534-547

[4] Decoding the genetic and epigenetic basis of asthma [J].

Stikker, Bernard S. ;

Hendriks, Rudi W. ;

Stadhouders, Ralph .

ALLERGY, 2023, 78 (04) :940-956

[5] Leveraging -omics for asthma endotyping [J].

Tyler, Scott R. ;

Bunyavanich, Supinda .

JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY, 2019, 144 (01) :13-24

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