AIMC Topic: Infant
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Prediction of outpatient visits for allergic rhinitis using an artificial intelligence LSTM model - a study in Eastern China.
BMC public health
Apr 9, 2025
BACKGROUND: Allergic rhinitis is a common disease that can affect the health of patients and bring huge social and economic burdens. In this study, we developed a model to predict the incidence rate of allergic rhinitis so as to provide accurate info...
Improving image quality on pediatric and neonatal radiography using AI-based compensation for image degradation.
Japanese journal of radiology
Apr 7, 2025
PURPOSE: To evaluate the impact of an AI-based, noise reduction technique for compensation of image degradation on pediatric and neonatal chest and abdomen radiography using a visual grading analysis.
Transformer-based deep learning ensemble framework predicts autism spectrum disorder using health administrative and birth registry data.
Scientific reports
Apr 7, 2025
Early diagnosis and access to resources, support and therapy are critical for improving long-term outcomes for children with autism spectrum disorder (ASD). ASD is typically detected using a case-finding approach based on symptoms and family history,...
Prediction of moderate to severe bleeding risk in pediatric immune thrombocytopenia using machine learning.
European journal of pediatrics
Apr 7, 2025
UNLABELLED: This study aimed to develop and validate a risk prediction model for moderate to severe bleeding in children with immune thrombocytopenia (ITP). Data from 286 ITP patients were prospectively collected and randomly split into training (80%...
Predicting hospital admissions, ICU utilization, and prolonged length of stay among febrile pediatric emergency department patients using incomplete and imbalanced electronic health record (EHR) data strategies.
International journal of medical informatics
Apr 4, 2025
OBJECTIVE: Determine the efficacy of commonly used approaches to handling missing and/or imbalanced Electronic Health Record (EHR) data on the performance of predictive models targeting risk of admission, intensive care unit (ICU) use, or prolonged l...
Machine learning approach for dosage individualization of azithromycin in children with community-acquired pneumonia.
British journal of clinical pharmacology
Apr 3, 2025
AIMS: The uncertainty about the efficacy and safety of currently used azithromycin dosing regimens in children warrants individualized therapy. The area under the plasma concentration-time curve over 24 h (AUC) of azithromycin correlates best with it...
Humans
Community-Acquired Pneumonia
Child, Preschool
Child
Dose-Response Relationship, Drug
Pneumonia
Female
Azithromycin
Male
Machine Learning
Drug Dosage Calculations
Infant
Area Under Curve
Algorithms
Community-Acquired Infections
Adolescent
Models, Biological
Anti-Bacterial Agents
Precision Medicine
A machine learning model to predict intradialytic hypotension in pediatric continuous kidney replacement therapy.
Pediatric nephrology (Berlin, Germany)
Apr 3, 2025
BACKGROUND: Intradialytic hypotension (IDH) is associated with mortality in adults undergoing intermittent hemodialysis, but this relationship is unclear in critically ill children receiving continuous kidney replacement therapy (CKRT). We aim to eva...
Evaluation of correctness and reliability of GPT, Bard, and Bing chatbots' responses in basic life support scenarios.
Scientific reports
Apr 3, 2025
Timely recognition and initiation of basic life support (BLS) before emergency medical services arrive significantly improve survival rates and neurological outcomes. In an era where health information-seeking behaviors have shifted toward online sou...
Forecasting motion trajectories of elbow and knee joints during infant crawling based on long-short-term memory (LSTM) networks.
Biomedical engineering online
Apr 2, 2025
BACKGROUND: Hands-and-knees crawling is a promising rehabilitation intervention for infants with motor impairments, while research on assistive crawling devices for rehabilitation training was still in its early stages. In particular, precisely gener...
Interpretable machine learning model for early prediction of disseminated intravascular coagulation in critically ill children.
Scientific reports
Apr 2, 2025
Disseminated intravascular coagulation (DIC) is a thrombo-hemorrhagic disorder that can be life-threatening in critically ill children, and the quest for an accurate and efficient method for early DIC prediction is of paramount importance. Candidate ...
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