AIMC Topic: Mothers

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Evaluation of incomplete maternal smoking data using machine learning algorithms: a study from the Medical Birth Registry of Norway.

BMC pregnancy and childbirth Nov 23, 2020
BACKGROUND: The Medical Birth Registry of Norway (MBRN) provides national coverage of all births. While retrieval of most of the information in the birth records is mandatory, mothers may refrain to provide information on her smoking status. The prop...
Marital Status Smoking Culture Mothers Linear Models Norway Female Educational Status Young Adult Adult Prevalence Registries Machine Learning Algorithms Pregnancy Humans
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The influence of maternal agency on severe child undernutrition in conflict-ridden Nigeria: Modeling heterogeneous treatment effects with machine learning.

PloS one Jan 9, 2019
Nigeria is one of the fastest growing African economies, yet struggles with armed conflict, poverty, and morbidity. An area of high concern is how this situation affects vulnerable families and their children. A key pathway in improving the situation...
Child Nutrition Disorders Female Humans Cross-Sectional Studies Child Machine Learning Nigeria Bayes Theorem Mothers
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Application of Neural Networks for classification of Patau, Edwards, Down, Turner and Klinefelter Syndrome based on first trimester maternal serum screening data, ultrasonographic findings and patient demographics.

BMC medical genomics Feb 13, 2018
BACKGROUND: The usage of Artificial Neural Networks (ANNs) for genome-enabled classifications and establishing genome-phenotype correlations have been investigated more extensively over the past few years. The reason for this is that ANNs are good ap...
Pregnancy Trimester, First Mothers Down Syndrome Demography Prenatal Diagnosis Female Trisomy 13 Syndrome Young Adult Adolescent Humans Adult Ultrasonography Neural Networks, Computer Computational Biology Pregnancy Trisomy 18 Syndrome Turner Syndrome Male Klinefelter Syndrome Middle Aged
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Evaluating the usability of an interactive, bi-lingual, touchscreen-enabled breastfeeding educational programme: application of Nielson's heuristics.

Journal of innovation in health informatics Mar 5, 2015
The study purpose was to conduct heuristic evaluation of an interactive, bilingual touchscreen-enabled breastfeeding educational programme for Hispanic women living in rural settings in Nebraska. Three raters conducted the evaluation during May 2013 ...
Rural Population Hispanic or Latino Breast Feeding Motivation Computer Heuristics Humans Mothers Multilingualism Female Health Education Software Data Display Adult Nebraska User-Computer Interface
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Using Machine Learning to Identify Predictors of Maternal and Infant Hair Cortisol Concentration Before and During the COVID-19 Pandemic.

Stress and health : journal of the International Society for the Investigation of Stress Jun 1, 2025
Hair cortisol concentration (HCC) has been theorized to reflect chronic stress, and maternal and infant HCC may be correlated due to shared genetic, physiological, behavioural, and environmental factors, such as stressful life circumstances. The curr...
Female Adult Infant COVID-19 Retrospective Studies Mothers Hair Hypothalamo-Hypophyseal System Stress, Psychological United States Hydrocortisone Humans Machine Learning
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Artificial intelligence-assisted chatbot: impact on breastfeeding outcomes and maternal anxiety.

BMC pregnancy and childbirth May 30, 2025
BACKGROUND: Artificial intelligence (AI) is increasingly used in healthcare interventions to provide accessible, continuous, and personalized patient support. This study investigates the impact of a mobile breastfeeding counseling application develop...
Female Young Adult Adult Humans Artificial Intelligence Mothers Postpartum Period Counseling Pamphlets Mobile Applications Generative Artificial Intelligence Anxiety Breast Feeding Self Efficacy
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