MIDO GDM: an innovative artificial intelligence-based prediction model for the development of gestational diabetes in Mexican women.
Sci Rep
; 13(1): 6992, 2023 04 28.
Article
em En
| MEDLINE
| ID: mdl-37117235
ABSTRACT
Given the barriers to early detection of gestational diabetes mellitus (GDM), this study aimed to develop an artificial intelligence (AI)-based prediction model for GDM in pregnant Mexican women. Data were retrieved from 1709 pregnant women who participated in the multicenter prospective cohort study 'Cuido mi embarazo'. A machine-learning-driven method was used to select the best predictive variables for GDM risk age, family history of type 2 diabetes, previous diagnosis of hypertension, pregestational body mass index, gestational week, parity, birth weight of last child, and random capillary glucose. An artificial neural network approach was then used to build the model, which achieved a high level of accuracy (70.3%) and sensitivity (83.3%) for identifying women at high risk of developing GDM. This AI-based model will be applied throughout Mexico to improve the timing and quality of GDM interventions. Given the ease of obtaining the model variables, this model is expected to be clinically strategic, allowing prioritization of preventative treatment and promising a paradigm shift in prevention and primary healthcare during pregnancy. This AI model uses variables that are easily collected to identify pregnant women at risk of developing GDM with a high level of accuracy and precision.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Diabetes Gestacional
/
Diabetes Mellitus Tipo 2
Tipo de estudo:
Clinical_trials
/
Diagnostic_studies
/
Etiology_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
/
Screening_studies
Limite:
Child
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Female
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Humans
/
Newborn
/
Pregnancy
País/Região como assunto:
Mexico
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article