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Child, Preschool

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Atrial Septal Defect Detection in Children Based on Ultrasound Video Using Multiple Instances Learning.

Journal of imaging informatics in medicine
Thoracic echocardiography (TTE) can provide sufficient cardiac structure information, evaluate hemodynamics and cardiac function, and is an effective method for atrial septal defect (ASD) examination. This paper aims to study a deep learning method b...

An artificial intelligence-driven predictive model for pediatric allogeneic hematopoietic stem cell transplantation using clinical variables.

European journal of haematology
BACKGROUND: Hematopoietic stem cell transplantation (HSCT) is a procedure with high morbidity and mortality. Identifying patients for maximum benefit and risk assessment is crucial in the decision-making process. This has led to the development of pr...

Comparing the Quality of Domain-Specific Versus General Language Models for Artificial Intelligence-Generated Differential Diagnoses in PICU Patients.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies
OBJECTIVES: Generative language models (LMs) are being evaluated in a variety of tasks in healthcare, but pediatric critical care studies are scant. Our objective was to evaluate the utility of generative LMs in the pediatric critical care setting an...

Predicting T-Cell Lymphoma in Children From F-FDG PET-CT Imaging With Multiple Machine Learning Models.

Journal of imaging informatics in medicine
This study aimed to examine the feasibility of utilizing radiomics models derived from F-FDG PET/CT imaging to screen for T-cell lymphoma in children with lymphoma. All patients had undergone F-FDG PET/CT scans. Lesions were extracted from PET/CT and...

AI-based diagnosis and phenotype - Genotype correlations in syndromic craniosynostoses.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Apert (AS), Crouzon (CS), Muenke (MS), Pfeiffer (PS), and Saethre Chotzen (SCS) are among the most frequently diagnosed syndromic craniosynostoses. The aims of this study were (1) to train an innovative model using artificial intelligence (AI)-based ...

Pediatric ECG-Based Deep Learning to Predict Left Ventricular Dysfunction and Remodeling.

Circulation
BACKGROUND: Artificial intelligence-enhanced ECG analysis shows promise to detect ventricular dysfunction and remodeling in adult populations. However, its application to pediatric populations remains underexplored.

Training intensity of robot-assisted gait training in children with cerebral palsy.

Developmental medicine and child neurology
AIM: We compared three different intensities of robot-assisted gait training (RAGT) for achieving favourable outcomes in children with cerebral palsy (CP).

Large-scale proteomics in the first trimester of pregnancy predict psychopathology and temperament in preschool children: an exploratory study.

Journal of child psychology and psychiatry, and allied disciplines
BACKGROUND: Understanding the prenatal origins of children's psychopathology is a fundamental goal in developmental and clinical science. Recent research suggests that inflammation during pregnancy can trigger a cascade of fetal programming changes t...

Rule-based deep learning method for prognosis of neonatal hypoxic-ischemic encephalopathy by using susceptibility weighted image analysis.

Magma (New York, N.Y.)
OBJECTIVE: Susceptibility weighted imaging (SWI) of neonatal hypoxic-ischemic brain injury can provide assistance in the prognosis of neonatal hypoxic-ischemic encephalopathy (HIE). We propose a convolutional neural network model to classify SWI imag...