AIMC Topic: Breast Feeding

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Predicting early cessation of exclusive breastfeeding using machine learning techniques.

PloS one
BACKGROUND: Identification of mother-infant pairs predisposed to early cessation of exclusive breastfeeding is important for delivering targeted support. Machine learning techniques enable development of transparent prediction models that enhance cli...

Development of Nipple Trauma Evaluation System With Deep Learning.

Journal of human lactation : official journal of International Lactation Consultant Association
BACKGROUND: No research has been conducted on the use of deep learning for breastfeeding support.

Trajectory of breastfeeding among Chinese women and risk prediction models based on machine learning: a cohort study.

BMC pregnancy and childbirth
BACKGROUND: Breastfeeding is the optimal source of nutrition for infants and young children, essential for their healthy growth and development. However, a gap in cohort studies tracking breastfeeding up to six months postpartum may lead caregivers t...

Artificial intelligence applied to the study of human milk and breastfeeding: a scoping review.

International breastfeeding journal
BACKGROUND: Breastfeeding rates remain below the globally recommended levels, a situation associated with higher infant and neonatal mortality rates. The implementation of artificial intelligence (AI) could help improve and increase breastfeeding rat...

Prediction of delayed breastfeeding initiation among mothers having children less than 2 months of age in East Africa: application of machine learning algorithms.

Frontiers in public health
BACKGROUND: Delayed breastfeeding initiation is a significant public health concern, and reducing the proportion of delayed breastfeeding initiation in East Africa is a key strategy for lowering the Child Mortality rate. However, there is limited evi...

Predicting mothers' exclusive breastfeeding for the first 6 months: Interface creation study using machine learning technique.

Journal of evaluation in clinical practice
BACKGROUND: Machine learning techniques (MLT) build models to detect complex patterns and solve new problems using big data.

Association between breastfeeding duration and diabetes mellitus in menopausal women: a machine-learning analysis using population-based retrospective study.

International breastfeeding journal
BACKGROUND: Breastfeeding resets insulin resistance caused by pregnancy however, studies on the association between breastfeeding and diabetes mellitus (DM) have reported inconsistent results. Therefore, we aimed to investigate the risk of DM accordi...

Application of Statistical Analysis and Machine Learning to Identify Infants' Abnormal Suckling Behavior.

IEEE journal of translational engineering in health and medicine
OBJECTIVE: Identify infants with abnormal suckling behavior from simple non-nutritive suckling devices.

Ethical Use of Artificial Intelligence for Scientific Writing: Current Trends.

Journal of human lactation : official journal of International Lactation Consultant Association

Predicting exclusive breastfeeding in maternity wards using machine learning techniques.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Adequate support in maternity wards is decisive for breastfeeding outcomes during the first year of life. Quality improvement interventions require the identification of the factors influencing hospital benchmark indicators....