Prediction of Gestational Diabetes Mellitus (GDM) risk in early pregnancy based on clinical data and ultrasound information: a nomogram

The nomogram model combining clinical data with 30° ultrasound data has good accuracy and clinical application value for predicting the risk of GDM.

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Publication Details

Journal
BMC Medical Informatics and Decision Making
Published
2025-03-18
DOI
https://doi.org/10.1186/s12911-025-02962-4
Citations
3
Primary Topic
Gestational Diabetes Research and Management
Type
article
Field-Weighted Citation Impact
6.17

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article

Prediction of Gestational Diabetes Mellitus (GDM) risk in early pregnancy based on clinical data and ultrasound information: a nomogram

Tong Zhu, Man Qin, Ling Chen, Wenwen Wang et al.
3 citations
BMC Medical Informatics and Decision Making
Gestational Diabetes Research and Management
6.17
article

Prediction of Gestational Diabetes Mellitus (GDM) risk in early pregnancy based on clinical data and ultrasound information: a nomogram

Tong Zhu, Man Qin, Ling Chen, Wenwen Wang, Lin Tang
article en
3 citations

Abstract

The nomogram model combining clinical data with 30° ultrasound data has good accuracy and clinical application value for predicting the risk of GDM.

BMC Medical Informatics and Decision MakingVol. 25(1)
First Affiliated Hospital of Shihezi University Medical College (CN)
Shihezi University, Xinjiang Production and Construction Corps
Good health and well-being
Openalex Percentile: Top 5%
Gestational Diabetes Research and Management
6.17
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