AIMC Topic: Infant

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Using machine learning to forecast peak health care service demand in real-time during the 2022-23 winter season: A pilot in England, UK.

PloS one Jan 27, 2025
During winter months, there is increased pressure on health care systems in temperature climates due to seasonal increases in respiratory illnesses. Providing real-time short-term forecasts of the demand for health care services helps managers plan t...
Health Services Needs and Demand Child, Preschool Emergency Service, Hospital Seasons Respiratory Syncytial Virus Infections Humans Infant Machine Learning Pilot Projects Forecasting England
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Plasma IL-17A is increased in patients with critical MIS-C and associated to in-hospital mortality.

Frontiers in immunology Jan 27, 2025
BACKGROUND: Multisystem inflammatory syndrome in children (MIS-C) is a rare and severe post-COVID-19 complication with multiple phenotypes.
Adolescent Child, Preschool Child Humans Interleukin-17 COVID-19 SARS-CoV-2 Hospital Mortality Prospective Studies ROC Curve Systemic Inflammatory Response Syndrome Biomarkers Male Intensive Care Units, Pediatric Female Infant Oxidative Stress Infant, Newborn
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Deep learning for forensic age estimation using orthopantomograms in children, adolescents, and young adults.

European radiology Jan 25, 2025
OBJECTIVES: Forensic age estimation from orthopantomograms (OPGs) can be performed more quickly and accurately using convolutional neural networks (CNNs), making them an ideal extension to standard forensic age estimation methods. This study evaluate...
Neural Networks, Computer Female Reproducibility of Results Young Adult Child, Preschool Male Humans Child Infant Radiography, Panoramic Deep Learning Age Determination by Teeth Adolescent
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Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine).

Scientific reports Jan 24, 2025
The COVID-19 pandemic has burdened healthcare systems globally. To curb high hospital admission rates, only patients with genuine medical needs are admitted. However, machine learning (ML) models to predict COVID-19 hospitalization in Asian children ...
Humans Machine Learning COVID-19 Algorithms Female Infant, Newborn SARS-CoV-2 Child, Preschool Hospitalization Child Male Malaysia Infant
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Predicting postoperative adhesive small bowel obstruction in infants under 3 months with intestinal malrotation: a random forest approach.

Jornal de pediatria Jan 21, 2025
OBJECTIVE: This study aimed to develop a predictive model using a random forest algorithm to determine the likelihood of postoperative adhesive small bowel obstruction (ASBO) in infants under 3 months with intestinal malrotation.
Intestinal Obstruction Intestine, Small Intestinal Volvulus Sensitivity and Specificity Male Retrospective Studies Humans ROC Curve Postoperative Complications Female Machine Learning Predictive Value of Tests Infant Infant, Newborn Algorithms Risk Factors Tissue Adhesions Random Forest
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Machine learning demonstrates clinical utility in distinguishing retinoblastoma from pseudo retinoblastoma with RetCam images.

Ophthalmic genetics Jan 20, 2025
BACKGROUND: Retinoblastoma is diagnosed and treated without biopsy based solely on appearance (with the indirect ophthalmoscope and imaging). More than 20 benign ophthalmic disorders resemble retinoblastoma and errors in diagnosis continue to be made...
Diagnosis, Differential Retinal Neoplasms Neural Networks, Computer Humans Retinoblastoma Machine Learning Female Male Sensitivity and Specificity Infant Child, Preschool Child
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Predicting stunting status among under-5 children in Rwanda using neural network model: Evidence from 2020 Rwanda demographic and health survey.

F1000Research Jan 20, 2025
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...
Child, Preschool Health Surveys Male Humans Infant Rwanda Neural Networks, Computer Growth Disorders Female
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Predicting fall parameters from infant skull fractures using machine learning.

Biomechanics and modeling in mechanobiology Jan 18, 2025
When infants are admitted to the hospital with skull fractures, providers must distinguish between cases of accidental and abusive head trauma. Limited information about the incident is available in such cases, and witness statements are not always r...
Skull Fractures Finite Element Analysis Humans Machine Learning Infant Accidental Falls
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Factors Associated with Abusive Head Trauma in Young Children Presenting to Emergency Medical Services Using a Large Language Model.

Prehospital emergency care Jan 17, 2025
OBJECTIVES: Abusive head trauma (AHT) is a leading cause of death in young children. Analyses of patient characteristics presenting to Emergency Medical Services (EMS) are often limited to structured data fields. Artificial Intelligence (AI) and Larg...
Humans Artificial Intelligence Retrospective Studies Female Natural Language Processing Large Language Models Craniocerebral Trauma Child Abuse Male Infant Child, Preschool Emergency Medical Services
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Derivation and validation of a clinical predictive model for longer duration diarrhea among pediatric patients in Kenya using machine learning algorithms.

BMC medical informatics and decision making Jan 15, 2025
BACKGROUND: Despite the adverse health outcomes associated with longer duration diarrhea (LDD), there are currently no clinical decision tools for timely identification and better management of children with increased risk. This study utilizes machin...
Child, Preschool Diarrhea Kenya Humans Machine Learning Algorithms Female Male Infant
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