AIMC Topic: Infant

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Predicting infant brain connectivity with federated multi-trajectory GNNs using scarce data.

Medical image analysis Mar 13, 2025
The understanding of the convoluted evolution of infant brain networks during the first postnatal year is pivotal for identifying the dynamics of early brain connectivity development. Thanks to the valuable insights into the brain's anatomy, existing...
Humans Infant Deep Learning Magnetic Resonance Imaging Connectome Brain Infant, Newborn
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Deep learning algorithm classification of tympanostomy tube images from a heterogenous pediatric population.

International journal of pediatric otorhinolaryngology Mar 13, 2025
IMPORTANCE: The ability to augment routine post-operative tube check appointments with at-home digital otoscopes and deep learning AI could improve health care access as well as reduce financial and time burden on families.
Otoscopes Humans Algorithms Prospective Studies Female Child Tympanic Membrane Middle Ear Ventilation Ear Canal Otoscopy Male Infant Deep Learning Child, Preschool
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Artificial intelligence for weight estimation in paediatric emergency care.

BMJ paediatrics open Mar 12, 2025
OBJECTIVE: To develop and validate a paediatric weight estimation model adapted to the characteristics of the Spanish population as an alternative to currently extended methods.
Child, Preschool Child Body Mass Index Emergency Medical Services Spain Body Weight Anthropometry Female Male Infant Adolescent Humans Artificial Intelligence Machine Learning
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An interpretable machine learning-assisted diagnostic model for Kawasaki disease in children.

Scientific reports Mar 7, 2025
Kawasaki disease (KD) is a syndrome of acute systemic vasculitis commonly observed in children. Due to its unclear pathogenesis and the lack of specific diagnostic markers, it is prone to being confused with other diseases that exhibit similar sympto...
Humans Machine Learning Area Under Curve Child, Preschool Algorithms Child Female ROC Curve Male Mucocutaneous Lymph Node Syndrome Infant
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Comparison of Machine Learning Algorithms Identifying Children at Increased Risk of Out-of-Home Placement: Development and Practical Considerations.

Health services research Mar 6, 2025
OBJECTIVE: To develop a machine learning (ML) algorithm capable of identifying children at risk of out-of-home placement among a Medicaid-insured population.
Female Male Risk Assessment Infant Adolescent Humans Machine Learning Algorithms Retrospective Studies United States Foster Home Care Medicaid Ohio Accountable Care Organizations Child, Preschool Child ROC Curve Logistic Models
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Development and Validation of an Electronic Health Record-Based, Pediatric Acute Respiratory Distress Syndrome Subphenotype Classifier Model.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Mar 6, 2025
OBJECTIVE: To determine if hyperinflammatory and hypoinflammatory pediatric acute respiratory distress syndrome (PARDS) subphenotypes defined using serum biomarkers can be determined solely from electronic health record (EHR) data using machine learn...
ROC Curve Respiratory Distress Syndrome Retrospective Studies Electronic Health Records Female Male Child, Preschool Child Intensive Care Units, Pediatric Infant Adolescent Humans Machine Learning Phenotype Biomarkers
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Prediction of malnutrition in kids by integrating ResNet-50-based deep learning technique using facial images.

Scientific reports Mar 6, 2025
In recent times, severe acute malnutrition (SAM) in India is considered a serious issue as per UNICEF 2022 records. In that record, 35.5% of children under age 5 are stunted, 19.3% are wasted, and 32% are underweight. Malnutrition, defined as these t...
Image Processing, Computer-Assisted Body Mass Index Malnutrition Face Humans Female Male Child, Preschool Child Infant India Deep Learning
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Construction and validation of a predictive model for meningoencephalitis in pediatric scrub typhus based on machine learning algorithms.

Emerging microbes & infections Mar 5, 2025
To retrospectively analyze the clinical characteristics of pediatric scrub typhus (ST) with meningoencephalitis (STME) and to construct and validate predictive models using machine learning.Clinical data were collected from 100 cases of pediatric STM...
Humans Adolescent Child, Preschool Child Bayes Theorem Scrub Typhus Meningoencephalitis Doxycycline Azithromycin Female Orientia tsutsugamushi Machine Learning Risk Factors Algorithms Male Anti-Bacterial Agents Infant Retrospective Studies
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Exploring the achievements and forecasting of SDG 3 using machine learning algorithms: Bangladesh perspective.

PloS one Mar 4, 2025
BACKGROUND: Sustainable Development Goal 3 (SDG 3), focusing on ensuring healthy lives and well-being for all, holds global significance and is particularly vital for Bangladesh. Neonatal Mortality Rate (NMR), Under-5 Mortality Rate (U5MR), Maternal ...
Child, Preschool Forecasting Child Mortality Female Humans Neural Networks, Computer Machine Learning Algorithms Bangladesh Maternal Mortality Infant Mortality Sustainable Development Infant, Newborn Infant
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Development and validation of a deep learning algorithm for prediction of pediatric recurrent intussusception in ultrasound images and radiographs.

BMC medical imaging Mar 3, 2025
PURPOSES: To develop a predictive model for recurrent intussusception based on abdominal ultrasound (US) images and abdominal radiographs.
Retrospective Studies Female Male Infant Humans Algorithms ROC Curve Recurrence Intussusception Radiography, Abdominal Deep Learning Child, Preschool Child Ultrasonography
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