AIMC Topic: Child

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Diagnosis of approximal caries in children with convolutional neural networks based detection algorithms on radiographs: A pilot study.

Acta odontologica Scandinavica
OBJECTIVES: Approximal caries diagnosis in children is difficult, and artificial intelligence-based research in pediatric dentistry is scarce. To create a convolutional neural network (CNN)-based diagnostic system for the prompt and efficient identif...

Early detection of autism spectrum disorder: gait deviations and machine learning.

Scientific reports
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder diagnosed by clinicians and experts through questionnaires, observations, and interviews. Current diagnostic practices focus on social and communication impairments, which often emerge l...

Personalized stress optimization intervention to reduce adolescents' anxiety: A randomized controlled trial leveraging machine learning.

Journal of anxiety disorders
Anxiety symptoms are among the most prevalent mental health disorders in adolescents, highlighting the need for scalable and accessible interventions. As anxiety often co-occurs with perceived stress during adolescence, stress interventions may offer...

Intelligent measurement of adolescent idiopathic scoliosis x-ray coronal imaging parameters based on VB-Net neural network: a retrospective analysis of 2092 cases.

Journal of orthopaedic surgery and research
BACKGROUND: Adolescent idiopathic scoliosis (AIS) is a complex three-dimensional deformity, and up to now, there has been no literature reporting the analysis of a large sample of X-ray imaging parameters based on artificial intelligence (AI) for it....

Psychotropic medications: a descriptive study of prescription trends in Tabriz, Iran, 2021-2022.

BMC psychiatry
INTRODUCTION: Mental disorders, such as anxiety and depression, significantly impacted global populations in 2019 and 2020, with COVID-19 causing a surge in prevalence. They affect 13.4% of the people worldwide, and 21% of Iranians have experienced t...

Multiparametric MRI along with machine learning predicts prognosis and treatment response in pediatric low-grade glioma.

Nature communications
Pediatric low-grade gliomas (pLGGs) exhibit heterogeneous prognoses and variable responses to treatment, leading to tumor progression and adverse outcomes in cases where complete resection is unachievable. Early prediction of treatment responsiveness...

Exploring cultural imaginaries of robots with children with brittle bone disease: a participatory design study.

Medical humanities
A symbiotic relationship exists between narrative imaginaries of and real-life advancements in technology. Such cultural imaginings have a powerful influence on our understanding of the potential that technology has to affect our lives; as a result, ...

The Minds We Make: A Philosophical Inquiry into Theory of Mind and Artificial Intelligence.

Integrative psychological & behavioral science
This theoretical paper offers an in-depth examination of the intersection between Theory of Mind (ToM) and artificial intelligence (AI), drawing on developmental psychology and philosophical analysis. By investigating the key developmental stages at ...

Application of machine learning in predicting postoperative arrhythmia following transcatheter closure of perimembranous ventricular septal defects.

Kardiologia polska
BACKGROUND: Arrhythmia is a frequent complication following transcatheter device closure of perimembranous ventricular septal defects (pmVSD). However, there is currently a lack of a convenient tool for predicting postoperative arrhythmia.