A PREDICTIVE CARE FRAMEWORK FOR DIABETES & MATERNAL HEALTH: A MACHINE LEARNING APPROACH FROM PRECONCEPTION THROUGH POSTPARTUM PERIOD
Ph.D
Saved in:
Main Author: | P MUKKESH KUMAR |
---|---|
Other Authors: | DEAN'S OFFICE (SSH SCH OF PUBLIC HEALTH) |
Format: | Theses and Dissertations |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://scholarbank.nus.edu.sg/handle/10635/235772 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | National University of Singapore |
Language: | English |
Similar Items
-
A nutritional supplement taken during preconception and pregnancy influences human milk macronutrients in women with overweight/obesity and gestational diabetes mellitus.
by: Han, Soo Min, et al.
Published: (2023) -
Maternal glycemic status during pregnancy and mid-childhood plasma amino acid profiles: findings from a multi-ethnic Asian birth cohort
by: Liu, Mengjiao, et al.
Published: (2024) -
Machine Learning-Derived Prenatal Predictive Risk Model to Guide Intervention and Prevent the Progression of Gestational Diabetes Mellitus to Type 2 Diabetes: Prediction Model Development Study
by: Kumar M., et al.
Published: (2023) -
EXPLORING THE DETERMINANTS AND UNDERLYING BELIEFS OF PREVENTIVE HEALTH BEHAVIOURS AMONG WOMEN WITH HISTORY OF GESTATIONAL DIABETES MELLITUS IN SINGAPORE: A MIXED METHODS STUDY
by: ANG MEI QI
Published: (2021) -
Impact of adopting the 2013 World Health Organization criteria for diagnosis of gestational diabetes in a multi-ethnic Asian cohort: A prospective study
by: CLAUDIA CHI, et al.
Published: (2018)