AIMC Topic: Child, Preschool
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Using machine learning to identify features associated with different types of self-injurious behaviors in autistic youth.
Psychological medicine
Mar 31, 2025
BACKGROUND: Self-injurious behaviors (SIB) are common in autistic people. SIB is mainly studied as a broad category, rather than by specific SIB types. We aimed to determine associations of distinct SIB types with common psychiatric, emotional, medic...
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 ...
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).
Machine Learning Analysis of Videourodynamics to Predict Incident Hydronephrosis in Patients With Spina Bifida.
The Journal of urology
Mar 25, 2025
PURPOSE: Variability in the interpretation of videourodynamics studies limits reliable classification of kidney injury risk for patients with spina bifida. We developed machine learning models to predict incident hydronephrosis in patients with spina...
Improving machine learning models through explainable AI for predicting the level of dietary diversity among Ethiopian preschool children.
Italian journal of pediatrics
Mar 24, 2025
BACKGROUND: Child nutrition in Ethiopia is a significant concern, particularly for preschool-aged children. Children must have a varied diet to ensure they receive all the essential nutrients for good health. Unfortunately, many children in Ethiopia ...
Machine learning-based radiomics using MRI to differentiate early-stage Duchenne and Becker muscular dystrophy in children.
BMC musculoskeletal disorders
Mar 22, 2025
OBJECTIVES: Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) present similar symptoms in the early stage, complicating their differentiation. This study aims to develop a classification model using radiomic features from MRI T2-w...
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