BACKGROUND: Stunting is a serious public health concern in Rwanda, affecting around 33.3% of children under five in 2020. The researchers have employed machine learning algorithms to predict stunting in Rwanda; however, few studies used ANNs, despite...
BACKGROUND: Short stature is a prevalent pediatric endocrine disorder for which early detection and prediction are pivotal for improving treatment outcomes. However, existing diagnostic criteria often lack the necessary sensitivity and specificity be...
BMC medical informatics and decision making
35794586
BACKGROUND: Our aim was to develop a machine learning model, using real-world data captured from a connected auto-injector device and from early indicators from the first 3 months of treatment, to predict sub-optimal adherence to recombinant human gr...
PURPOSE: The aims of the study were to develop and evaluate a machine learning model with which to predict postnatal growth failure (PGF) among very low birth weight (VLBW) infants.
BACKGROUND AND OBJECTIVES: Child undernutrition is a leading global health concern, especially in low and middle-income developing countries, including Bangladesh. Thus, the objectives of this study are to develop an appropriate model for predicting ...
RATIONALE AND OBJECTIVES: To develop an efficient machine-learning model using pituitary MRI radiomics and clinical data to differentiate growth hormone deficiency (GHD) from idiopathic short stature (ISS), making the diagnostic process more acceptab...
Nutrition (Burbank, Los Angeles County, Calif.)
39848008
OBJECTIVES: Childhood stunting remains a significant public health issue in India, affecting approximately 35% of children under 5. Despite extensive research, existing prediction models often fail to incorporate diverse data sources and address the ...
BMC medical informatics and decision making
39623435
INTRODUCTION: Stunting affects one-fifth of children globally with diarrhea accounting for an estimated 13.5% of stunting. Identifying risk factors for its precursor, linear growth faltering (LGF), is critical to designing interventions. Moreover, de...
BACKGROUND: Stunting is a vital indicator of chronic undernutrition that reveals a failure to reach linear growth. Investigating growth and nutrition status during adolescence, in addition to infancy and childhood is very crucial. However, the availa...
BACKGROUND: The multifaceted issue of childhood stunting in low- and middle-income countries has a profound and enduring impact on children's well-being, cognitive development, and future earning potential. Childhood stunting arises from a complex in...