AIMC Topic: Child

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Letter Tracing: a Serious Game to Teach Handwriting and Assess Proficiency through Machine Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This work introduces the "Letter Tracing", a serious game designed to teach correct letter formation. Co-designed through collaboration with clinicians and technicians, the game underwent testing with 9 first- and 26 second-grade children to assess i...

An Explainable and Conformal AI Model to Detect Temporomandibular Joint Involvement in Children Suffering from Juvenile Idiopathic Arthritis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease during childhood and adolescence. The temporomandibular joints (TMJ) are among the most frequently affected joints in patients with JIA, and mandibular growth is especially vuln...

Stepwise Transfer Learning for Expert-level Pediatric Brain Tumor MRI Segmentation in a Limited Data Scenario.

Radiology. Artificial intelligence
Purpose To develop, externally test, and evaluate clinical acceptability of a deep learning pediatric brain tumor segmentation model using stepwise transfer learning. Materials and Methods In this retrospective study, the authors leveraged two T2-wei...

Automatic diagnosis of pediatric supracondylar humerus fractures using radiomics-based machine learning.

Medicine
The aim of this study was to construct a classification model for the automatic diagnosis of pediatric supracondylar humerus fractures using radiomics-based machine learning. We retrospectively collected elbow joint Radiographs of children aged 3 to ...

Unraveling the complexity of the senescence-associated secretory phenotype in adamantinomatous craniopharyngioma using multimodal machine learning analysis.

Neuro-oncology
BACKGROUND: Cellular senescence can have positive and negative effects on the body, including aiding in damage repair and facilitating tumor growth. Adamantinomatous craniopharyngioma (ACP), the most common pediatric sellar/suprasellar brain tumor, p...

Machine learning trial to detect sex differences in simple sticker arts of 1606 preschool children.

Minerva pediatrics
BACKGROUND: Previous studies suggested that drawings made by preschool boys and girls show distinguishable differences. However, children's drawings on their own are too complexly determined and inherently ambiguous to be a reliable indicator. In the...

Predicting type 1 diabetes in children using electronic health records in primary care in the UK: development and validation of a machine-learning algorithm.

The Lancet. Digital health
BACKGROUND: Children presenting to primary care with suspected type 1 diabetes should be referred immediately to secondary care to avoid life-threatening diabetic ketoacidosis. However, early recognition of children with type 1 diabetes is challengin...