AIMC Topic: Child
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Contemporary digital marketing techniques used in unhealthy food campaigns targeting young people.
Appetite
Apr 2, 2025
The digital marketing of unhealthy foods and non-alcoholic beverages has a detrimental impact on children's eating behaviours, leading to adverse diet-related health outcomes. To inform the development of evidence-based strategies to protect children...
Stakeholder acceptance of a robot-assisted social training scenario for autistic children compared to a tablet-computer-based approach.
Scientific reports
Apr 2, 2025
Recent studies indicate the potential benefits of robot-assisted therapy (RAT) for children on the autism spectrum (AS), yet acceptance among stakeholders remains unclear due to methodological shortcomings in existing research. This study evaluates s...
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 ...
Trade-off of different deep learning-based auto-segmentation approaches for treatment planning of pediatric craniospinal irradiation autocontouring of OARs for pediatric CSI.
Medical physics
Apr 1, 2025
BACKGROUND: As auto-segmentation tools become integral to radiotherapy, more commercial products emerge. However, they may not always suit our needs. One notable example is the use of adult-trained commercial software for the contouring of organs at ...
Development and validation of a machine learning model for predicting pediatric metabolic syndrome using anthropometric and bioelectrical impedance parameters.
International journal of obesity (2005)
Apr 1, 2025
OBJECTIVE: Metabolic syndrome (MS) is a risk factor for cardiovascular diseases, and its prevalence is increasing among children and adolescents. This study developed a machine learning model to predict MS using anthropometric and bioelectrical imped...
Enhancing brain age estimation under uncertainty: A spectral-normalized neural gaussian process approach utilizing 2.5D slicing.
NeuroImage
Apr 1, 2025
Brain age gap, the difference between estimated brain age and chronological age via magnetic resonance imaging, has emerged as a pivotal biomarker in the detection of brain abnormalities. While deep learning is accurate in estimating brain age, the a...
Automatic detection of developmental stages of molar teeth with deep learning.
BMC oral health
Apr 1, 2025
BACKGROUND: The aim was to fully automate molar teeth developmental staging and to comprehensively analyze a wide range of deep learning models' performances for molar tooth germ detection on panoramic radiographs.
Can we use lower extremity joint moments predicted by the artificial intelligence model during walking in patients with cerebral palsy in the clinical gait analysis?
PloS one
Apr 1, 2025
Several studies have highlighted the advantages of employing artificial intelligence (AI) models in gait analysis. However, the credibility and practicality of integrating these models into clinical gait routines remain uncertain. This study critical...
Leveraging large language models to mimic domain expert labeling in unstructured text-based electronic healthcare records in non-english languages.
BMC medical informatics and decision making
Mar 31, 2025
BACKGROUND: The integration of big data and artificial intelligence (AI) in healthcare, particularly through the analysis of electronic health records (EHR), presents significant opportunities for improving diagnostic accuracy and patient outcomes. H...
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...
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