AIMC Topic: Child

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Enhancing brain age estimation under uncertainty: A spectral-normalized neural gaussian process approach utilizing 2.5D slicing.

NeuroImage
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
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
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...

A Tunable Forced Alignment System Based on Deep Learning: Applications to Child Speech.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: Phonetic forced alignment has a multitude of applications in automated analysis of speech, particularly in studying nonstandard speech such as children's speech. Manual alignment is tedious but serves as the gold standard for clinical-grade ...

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
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
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
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
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 ...

Artificial intelligence-quantified schisis volume as a structural endpoint for gene therapy clinical trials in X-linked retinoschisis.

Acta ophthalmologica
PURPOSE: To use artificial intelligence (AI) for quantifying schisis volume (ASV) in X-linked retinoschisis (XLRS) for use as a structural endpoint in gene therapy clinical trials.

The future of paediatric sleep medicine: a blueprint for advancing the field.

Journal of sleep research
Paediatric sleep medicine has rapidly evolved and expanded over the past half century as it became increasingly recognised as a unique field related to but distinct from adult sleep medicine. In looking forward to the next years, the focus of the fol...