ArticleScientific reports2023
MIDO GDM: an innovative artificial intelligence-based prediction model for the development of gestational diabetes in Mexican women.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 28 citations in OpenAlex.
- How the First 9 Months Shape the Rest of Your Life: The Impact of Gestational Diabetes on the Metabolic Future.Diabetes, obesity & metabolism · 2026Review
- Redox Imbalance in Gestational Diabetes Mellitus: Mechanistic Insights, Emerging Biomarkers, and Therapeutic Perspectives.International journal of molecular sciences · 2026Review
- Predictive performance of artificial intelligence algorithms for gestational diabetes mellitus in pregnant women: a protocol for systematic review and meta-analysis.Systematic reviews · 2026Article
- Precision Medicine and Shared Decision-Making to Advance Gestational Diabetes Management: Genetic, Metabolic, and Gut Microbiota Factors.Patient preference and adherence · 2026Review
- Development and multicenter validation of a novel model for selective screening of gestational diabetes mellitus: the Vietnam gestational diabetes mellitus study.BMC pregnancy and childbirth · 2025Article
- Artificial Intelligence in Gestational Diabetes Care: A Systematic Review.Journal of diabetes science and technology · 2025Review
- Artificial Intelligence Enabled Lifestyle Medicine in Diabetes Care: A Narrative Review.American journal of lifestyle medicine · 2025Review
- Insights into the Global and Mexican Context of Placental-Derived Pregnancy Complications.Biomedicines · 2025Review
- Association between cardiometabolic index and gestational diabetes mellitus: a cross-sectional study.Endocrine · 2025Article
- Patient-Centred Gestational Diabetes Care: Preference Elicitation Methods and Machine Learning Innovations.Patient preference and adherence · 2025Review
- Innovative development of territories based on the integrated use of social, resource and environmental potential.Scientific reports · 2024Article
- Artificial Neural Networks to Predict Metabolic Syndrome without Invasive Methods in Adolescents.Journal of clinical medicine · 2024Article
- The early prediction of gestational diabetes mellitus by machine learning models.BMC pregnancy and childbirth · 2024Article
- The role of machine learning algorithms in detection of gestational diabetes; a narrative review of current evidence.Clinical diabetes and endocrinology · 2024Review
- Review of Genetic and Artificial Intelligence approaches to improving Gestational Diabetes Mellitus Screening and Diagnosis in sub-Saharan Africa.The Yale journal of biology and medicine · 2024Review
- Gestational Diabetes Mellitus Subtypes Classified by Oral Glucose Tolerance Test and Maternal and Perinatal Outcomes: Results of a Mexican Multicenter Prospective Cohort Study "Cuido Mi Embarazo".Diabetes, metabolic syndrome and obesity : targets and therapy · 2024Article
Corrections and comments
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Authors and funding
22 authors at 7 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.