Predicting postpartum glucose intolerance in women with gestational diabetes mellitus in primary care: A machine learning approach using XGBoost and SHAP values

Nur Aiza Idris; Nurul Azreen Yusof; Muhd Zulfadli Hafiz Ismail; Siti Norazlina Juhari; Nurulhuda Mat Hassan; Norwati Daud; Nurul Izza Yunus; Mohd Faeiz Pauzi

doi:10.1016/j.diabres.2026.113098

Predicting postpartum glucose intolerance in women with gestational diabetes mellitus in primary care: A machine learning approach using XGBoost and SHAP values

Diabetes Research and Clinical Practice 2026

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Authors: Nur Aiza Idris, Nurul Azreen Yusof, Muhd Zulfadli Hafiz Ismail, Siti Norazlina Juhari, Nurulhuda Mat Hassan, Norwati Daud, Nurul Izza Yunus, Mohd Faeiz Pauzi

DOI: 10.1016/j.diabres.2026.113098

Cited by: 2

References: 38

Fields of Study & Subjects

Gestational Diabetes Research and Management Artificial Intelligence in Healthcare Hyperglycemia and glycemic control in critically ill and hospitalized patients

Publication details

Journal / source: Diabetes Research and Clinical Practice
Publisher: Elsevier BV
Volume: 232
Pages: 113098–113098
Publication date: 13 January 2026
Language: EN

References 38