AIMC Topic: Infant

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Impact of deep learning on pediatric elbow fracture detection: a systematic review and meta-analysis.

European journal of trauma and emergency surgery : official publication of the European Trauma Society Feb 20, 2025
OBJECTIVES: Pediatric elbow fractures are a common injury among children. Recent advancements in artificial intelligence (AI), particularly deep learning (DL), have shown promise in diagnosing these fractures. This study systematically evaluated the ...
Fractures, Bone Elbow Injuries Elbow Fractures Deep Learning Adolescent Child, Preschool Humans Child Sensitivity and Specificity Infant
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SegFormer3D: Improving the Robustness of Deep Learning Model-Based Image Segmentation in Ultrasound Volumes of the Pediatric Hip.

Ultrasound in medicine & biology Feb 19, 2025
Developmental dysplasia of the hip (DDH) is a painful orthopedic malformation diagnosed at birth in 1-3% of all newborns. Left untreated, DDH can lead to significant morbidity including long-term disability. Currently the condition is clinically diag...
Infant Deep Learning Ultrasonography Developmental Dysplasia of the Hip Imaging, Three-Dimensional Humans Female Infant, Newborn Male
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Deep learning-based automated guide for defining a standard imaging plane for developmental dysplasia of the hip screening using ultrasonography: a retrospective imaging analysis.

BMC medical informatics and decision making Feb 18, 2025
BACKGROUND: We aimed to propose a deep-learning neural network model for automatically detecting five landmarks during a two-dimensional (2D) ultrasonography (US) scan to develop a standard plane for developmental dysplasia of the hip (DDH) screening...
Male Humans Anatomic Landmarks Infant Neural Networks, Computer Deep Learning Developmental Dysplasia of the Hip Retrospective Studies Ultrasonography Female
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Effectiveness of social robots in improving psychological well-being of hospitalised children: A systematic review and meta-analysis.

Journal of pediatric nursing Feb 17, 2025
AIM: To evaluate the effectiveness of social robots in reducing pain, stress, and anxiety among hospitalised children.
Humans Female Pain Management Child, Hospitalized Stress, Psychological Psychological Well-Being Male Child, Preschool Infant Child Anxiety Robotics
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An explainable and accurate transformer-based deep learning model for wheeze classification utilizing real-world pediatric data.

Scientific reports Feb 15, 2025
Auscultation is a method that involves listening to sounds from the patient's body, mainly using a stethoscope, to diagnose diseases. The stethoscope allows for non-invasive, real-time diagnosis, and it is ideal for diagnosing respiratory diseases an...
Stethoscopes Auscultation Respiratory Sounds Deep Learning Child, Preschool Child Humans Prospective Studies Republic of Korea Female Male Infant
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Predictive modeling of methadone poisoning outcomes in children ≤ 5 years: utilizing machine learning and the National Poison Data System for improved clinical decision-making.

European journal of pediatrics Feb 11, 2025
UNLABELLED: The escalating therapeutic use of methadone has coincided with an increase in accidental ingestions, particularly among children ≤ 5 years. This study utilized machine learning (ML) methodologies on data from the National Poison Data Syst...
Humans Male Infant Child, Preschool Methadone Machine Learning Retrospective Studies Clinical Decision-Making Female Poison Control Centers
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Feature gene selection and functional validation of SH3KBP1 in infantile hemangioma using machine learning.

Biochemical and biophysical research communications Feb 10, 2025
BACKGROUND: Infantile hemangioma (IH) is a prevalent vascular tumor in infancy with a complex pathogenesis that remains unclear. This study aimed to investigate the underlying mechanisms of IH using comprehensive bioinformatics analyses and in vitro ...
Hemangioma Computational Biology Gene Expression Regulation, Neoplastic MicroRNAs Adaptor Proteins, Signal Transducing Gene Expression Profiling Child, Preschool Gene Regulatory Networks Humans Machine Learning Female Male Infant
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Interpretable machine learning-derived nomogram model for early detection of persistent diarrhea in Salmonella typhimurium enteritis: a propensity score matching based case-control study.

BMC infectious diseases Feb 10, 2025
BACKGROUND: Salmonella typhimurium infection is a considerable global health concern, particularly in children, where it often leads to persistent diarrhea. This condition can result in severe health complications including malnutrition and cognitive...
Infant Case-Control Studies Child, Preschool Child Diarrhea Early Diagnosis Nomograms Salmonella typhimurium Propensity Score Enteritis Salmonella Infections Retrospective Studies Female Risk Factors Male Humans Machine Learning
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Ultrasonic-Based Radiomics Signature With Machine Learning for Differentiating Prognostic Subsets of Pediatric Peripheral Neuroblastic Tumors: A Retrospective Study.

Ultrasound in medicine & biology Feb 8, 2025
OBJECTIVE: To construct and select a better model based on ultrasonic-based radiomics features and clinical characteristics for prognostic subsets of pediatric neuroblastic tumors.
Humans Machine Learning Prognosis Retrospective Studies Child, Preschool Child Female Ultrasonography Radiomics Neuroblastoma Male Infant
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Analyzing and forecasting under-5 mortality trends in Bangladesh using machine learning techniques.

PloS one Feb 7, 2025
BACKGROUND: Under-5 mortality remains a critical social indicator of a country's development and economic sustainability, particularly in developing nations like Bangladesh. This study employs machine learning models, including Linear Regression, Rid...
Child, Preschool Female Bayes Theorem Infant Mortality Humans Infant, Newborn Child Mortality Linear Models Machine Learning Male Bangladesh Forecasting Infant
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