AIMC Topic: Child
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Automated Autism Assessment With Multimodal Data and Ensemble Learning: A Scalable and Consistent Robot-Enhanced Therapy Framework.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 31, 2025
Navigating the complexities of Autism Spectrum Disorder (ASD) diagnosis and intervention requires a nuanced approach that addresses both the inherent variability in therapeutic practices and the imperative for scalable solutions. This paper presents ...
Multimodal contrastive learning for enhanced explainability in pediatric brain tumor molecular diagnosis.
Scientific reports
Mar 30, 2025
Despite the promising performance of convolutional neural networks (CNNs) in brain tumor diagnosis from magnetic resonance imaging (MRI), their integration into the clinical workflow has been limited. That is mainly due to the fact that the features ...
O blood usage trends in the pediatric population 2015-2019: A multi-institutional analysis.
Transfusion
Mar 28, 2025
BACKGROUND: In 2019, AABB released the bulletin "Recommendations on the Use of Group O Red Blood Cells" in which the recommendations about pediatric and neonatal blood transfusions were limited. Eight U.S. pediatric hospitals sought to determine tren...
Machine learning in lymphocyte and immune biomarker analysis for childhood thyroid diseases in China.
BMC pediatrics
Mar 28, 2025
OBJECTIVE: This study aims to characterize and analyze the expression of representative biomarkers like lymphocytes and immune subsets in children with thyroid disorders. It also intends to develop and evaluate a machine learning model to predict if ...
Machine learning-based risk prediction model for pertussis in children: a multicenter retrospective study.
BMC infectious diseases
Mar 27, 2025
BACKGROUND: Pertussis is a highly contagious respiratory disease. Even though vaccination has reduced the incidence, cases have resurfaced in certain regions due to immune escape and waning vaccine efficacy. Identifying high-risk patients to mitigate...
A prospective study for the examination of peripheral blood smear samples in pediatric population using artificial intelligence.
Turkish journal of medical sciences
Mar 27, 2025
BACKGROUND/AIM: Peripheral blood smear (PBS) and bone marrow aspiration are gold standards of manual microscopy diagnostics for blood cell disorders. Nowadays, data-driven artificial intelligence (AI) techniques open new perspectives in digital hemat...
A Novel Visual Model for Predicting Prognosis of Resected Hepatoblastoma: A Multicenter Study.
Academic radiology
Mar 26, 2025
RATIONALE AND OBJECTIVES: This study aimed to evaluate the application of a contrast-enhanced CT-based visual model in predicting postoperative prognosis in patients with hepatoblastoma (HB).
Deep learning based quantitative cervical vertebral maturation analysis.
Head & face medicine
Mar 26, 2025
OBJECTIVES: This study aimed to enhance clinical diagnostics for quantitative cervical vertebral maturation (QCVM) staging with precise landmark localization. Existing methods are often subjective and time-consuming, while deep learning alternatives ...
Integrating bioinformatics and machine learning for comprehensive analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric septic shock.
Scientific reports
Mar 26, 2025
This study aims to predict and diagnose pediatric septic shock through the screening of immune infiltration-related biomarkers. Three gene expression datasets were accessible from the Gene Expression Omnibus repository. The differentially expressed g...
Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection.
BMC psychiatry
Mar 26, 2025
OBJECTIVE: To develop a stratified screening tool through machine learning approaches for the Center for Epidemiologic Studies Depression Scale (CES-D-20) while maintaining diagnostic accuracy, addressing the efficiency limitations in large-scale app...
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