AIMC Topic: Infant
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Geographic inequities in neonatal survival in Nigeria: a cross-sectional evidence from spatial and artificial neural network analyses.
Journal of biosocial science
Sep 19, 2024
This study was conducted to provide empirical evidence of geographical variations of neonatal mortality and its associated social determinants with a view to improving neonatal survival at the subnational level in Nigeria. With a combination of spati...
An automated framework for pediatric hip surveillance and severity assessment using radiographs.
International journal of computer assisted radiology and surgery
Sep 16, 2024
PURPOSE: Hip dysplasia is the second most common orthopedic condition in children with cerebral palsy (CP) and may result in disability and pain. The migration percentage (MP) is a widely used metric in hip surveillance, calculated based on an anteri...
Machine learning-based evaluation of prognostic factors for mortality and relapse in patients with acute lymphoblastic leukemia: a comparative simulation study.
BMC medical informatics and decision making
Sep 16, 2024
BACKGROUND: Predicting mortality and relapse in children with acute lymphoblastic leukemia (ALL) is crucial for effective treatment and follow-up management. ALL is a common and deadly childhood cancer that often relapses after remission. In this stu...
Predictive performance of urinalysis for urine culture results according to causative microorganisms: an integrated analysis with artificial intelligence.
Journal of clinical microbiology
Sep 12, 2024
Urinary tract infections (UTIs) are pervasive and prevalent in both community and hospital settings. Recent trends in the changes of the causative microorganisms in these infections could affect the effectiveness of urinalysis (UA). We aimed to evalu...
CONSTRUCTING A DIAGNOSTIC PREDICTION MODEL TO ESTIMATE THE SEVERE RESPIRATORY SYNCYTIAL VIRUS PNEUMONIA IN CHILDREN BASED ON MACHINE LEARNING.
Shock (Augusta, Ga.)
Sep 11, 2024
Background : Severe respiratory syncytial virus (RSV) pneumonia is a leading cause of hospitalization and morbidity in infants and young children. Early identification of severe RSV pneumonia is crucial for timely and effective treatment by pediatric...
Development and validation of machine-learning models of diet management for hyperphenylalaninemia: a multicenter retrospective study.
BMC medicine
Sep 11, 2024
BACKGROUND: Assessing dietary phenylalanine (Phe) tolerance is crucial for managing hyperphenylalaninemia (HPA) in children. However, traditionally, adjusting the diet requires significant time from clinicians and parents. This study aims to investig...
A Predictive Model of Pressure Injury in Children Undergoing Living Donor Liver Transplantation Based on Machine Learning Algorithm.
Journal of advanced nursing
Sep 10, 2024
AIMS: The aim of our study was to formulate and validate a prediction model using machine learning algorithms to forecast the risk of pressure injuries (PIs) in children undergoing living donor liver transplantation (LDLT).
Proteomics profiling and machine learning in nusinersen-treated patients with spinal muscular atrophy.
Cellular and molecular life sciences : CMLS
Sep 10, 2024
AIM: The availability of disease-modifying therapies and newborn screening programs for spinal muscular atrophy (SMA) has generated an urgent need for reliable prognostic biomarkers to classify patients according to disease severity. We aim to identi...
Etiological stratification and prognostic assessment of haemophagocytic lymphohistiocytosis by machine learning on onco-mNGS data and clinical data.
Frontiers in immunology
Sep 9, 2024
INTRODUCTION: Hemophagocytic lymphohistiocytosis (HLH) is a rare, complicated and life threatening hyperinflammatory syndrome that maybe triggered by various infectious agents, malignancies and rheumatologic disorders. Early diagnosis and identificat...
A machine learning model for early diagnosis of type 1 Gaucher disease using real-life data.
Journal of clinical epidemiology
Sep 6, 2024
OBJECTIVE: The diagnosis of Gaucher disease (GD) presents a major challenge due to the high variability and low specificity of its clinical characteristics, along with limited physician awareness of the disease's early symptoms. Early and accurate di...
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