Lack of Data Sharing Despite Data Availability Statements in Studies Using Machine Learning Models for Prediction of Gestational Diabetes Mellitus.
作者信息
Germaine Mark, Healy Graham, Egan Brendan
机构信息
School of Computing, Dublin City University, Dublin, Ireland.
School of Health and Human Performance, Dublin City University, Dublin, Ireland.
出版信息
Diabetes Care. 2024 Oct 1;47(10):e78-e79. doi: 10.2337/dc24-1483.
Abstract
摘要
相似文献
1
Lack of Data Sharing Despite Data Availability Statements in Studies Using Machine Learning Models for Prediction of Gestational Diabetes Mellitus.在使用机器学习模型预测妊娠期糖尿病的研究中，尽管有数据可用性声明，但仍缺乏数据共享。
Diabetes Care. 2024 Oct 1;47(10):e78-e79. doi: 10.2337/dc24-1483.
2
Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study.使用常规临床数据的机器学习方法与传统逻辑回归预测妊娠期糖尿病的比较：一项回顾性队列研究。
J Diabetes Res. 2020 Jun 12;2020:4168340. doi: 10.1155/2020/4168340. eCollection 2020.
3
Early Prediction of Gestational Diabetes Mellitus in the Chinese Population via Advanced Machine Learning.基于先进机器学习的中国人群妊娠期糖尿病早期预测。
J Clin Endocrinol Metab. 2021 Mar 8;106(3):e1191-e1205. doi: 10.1210/clinem/dgaa899.
4
Machine learning risk score for prediction of gestational diabetes in early pregnancy in Tianjin, China.基于中国天津地区的早期妊娠孕妇机器学习风险评分预测妊娠期糖尿病
Diabetes Metab Res Rev. 2021 Jul;37(5):e3397. doi: 10.1002/dmrr.3397. Epub 2020 Sep 9.
5
Predicting the risk of gestational diabetes using clinical data with machine learning: a predictive model study.使用机器学习结合临床数据预测妊娠期糖尿病风险：一项预测模型研究
Am J Obstet Gynecol MFM. 2023 Jul;5(7):100965. doi: 10.1016/j.ajogmf.2023.100965. Epub 2023 Apr 8.
6
Prediction of gestational diabetes mellitus in Asian women using machine learning algorithms.基于机器学习算法预测亚洲女性妊娠期糖尿病。
Sci Rep. 2023 Aug 16;13(1):13356. doi: 10.1038/s41598-023-39680-8.
7
Population-centric risk prediction modeling for gestational diabetes mellitus: A machine learning approach.以人群为中心的妊娠糖尿病风险预测建模：一种机器学习方法。
Diabetes Res Clin Pract. 2022 Mar;185:109237. doi: 10.1016/j.diabres.2022.109237. Epub 2022 Feb 4.
8
Prediction of gestational diabetes mellitus using machine learning from birth cohort data of the Japan Environment and Children's Study.基于日本环境与儿童研究出生队列数据的机器学习预测妊娠糖尿病。
Sci Rep. 2023 Oct 13;13(1):17419. doi: 10.1038/s41598-023-44313-1.
9
Machine learning-based models for gestational diabetes mellitus prediction before 24-28 weeks of pregnancy: A review.基于机器学习的 24-28 孕周前妊娠糖尿病预测模型：综述。
Artif Intell Med. 2022 Oct;132:102378. doi: 10.1016/j.artmed.2022.102378. Epub 2022 Aug 24.
10
Open science practices need substantial improvement in prognostic model studies in oncology using machine learning.在利用机器学习进行肿瘤预后模型研究方面，开放科学实践需要大幅改进。
J Clin Epidemiol. 2024 Jan;165:111199. doi: 10.1016/j.jclinepi.2023.10.015. Epub 2023 Oct 28.
引用本文的文献
1
Label Accuracy in Electronic Health Records and Its Impact on Machine Learning Models for Early Prediction of Gestational Diabetes: 3-Step Retrospective Validation Study.电子健康记录中的标签准确性及其对妊娠期糖尿病早期预测机器学习模型的影响：三步回顾性验证研究
JMIR Med Inform. 2025 Aug 21;13:e72938. doi: 10.2196/72938.
本文引用的文献
1
Has open data arrived at the British Medical Journal (BMJ)? An observational study.开放数据是否已登陆《英国医学杂志》（BMJ）？一项观察性研究。
BMJ Open. 2016 Oct 13;6(10):e011784. doi: 10.1136/bmjopen-2016-011784.
2
A failed attempt to conduct an individual patient data meta-analysis.一次进行个体患者数据荟萃分析的失败尝试。
Syst Rev. 2014 Sep 4;3:97. doi: 10.1186/2046-4053-3-97.
3
The availability of research data declines rapidly with article age.研究数据的可用性随文章年龄的增长迅速下降。
Curr Biol. 2014 Jan 6;24(1):94-97. doi: 10.1016/j.cub.2013.11.014. Epub 2013 Dec 19.
Zotero 插件