AIMC Topic: Child

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ASSOCIATION OF TESSELLATION DENSITY WITH PROGRESSION OF AXIAL LENGTH AND REFRACTION IN CHILDREN: An Artificial Intelligence-Assisted 4-Year Study.

Retina (Philadelphia, Pa.)
PURPOSE: To investigate fundus tessellation density (TD) and its association with axial length (AL) elongation and spherical equivalent (SE) progression in children.

An electroencephalography-based sleep index and supervised machine learning as a suitable tool for automated sleep classification in children.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
STUDY OBJECTIVES: Although sleep is frequently disrupted in the pediatric intensive care unit, it is currently not possible to perform real-time sleep monitoring at the bedside. In this study, spectral band powers of electroencephalography data are u...

The League: A person-centred approach to the development of social robotics for paediatric anxiety.

Health expectations : an international journal of public participation in health care and health policy
BACKGROUND: Social robots are promising tools to improve the quality of life of children and youth living with anxiety and should be developed based on the priorities of end users. However, pathways to include young people in patient-oriented researc...

A Deep Learning-Based System for the Assessment of Dental Caries Using Colour Dental Photographs.

Studies in health technology and informatics
D1ental caries remains the most common chronic disease in childhood, affecting almost half of all children globally. Dental care and examination of children living in remote and rural areas is an ongoing challenge that has been compounded by COVID. T...

Artificial Intelligence Approach for Severe Dengue Early Warning System.

Studies in health technology and informatics
Dengue fever is a viral infectious disease transmitted through mosquito bites, and has symptoms ranging from mild flu-like symptoms to deadly complications. Dengue fever is one of the global burden diseases which annually have 50-100 million cases wi...

Utilization of Machine Learning Approaches to Predict Mortality in Pediatric Warzone Casualties.

Military medicine
BACKGROUND: Identification of pediatric trauma patients at the highest risk for death may promote optimization of care. This becomes increasingly important in austere settings with constrained medical capabilities. This study aimed to develop and val...

Current Applications of Artificial Intelligence for Pediatric Dentistry: A Systematic Review and Meta-Analysis.

Pediatric dentistry
To systematically evaluate artificial intelligence applications for diagnostic and treatment planning possibilities in pediatric dentistry. PubMed, EMBASE, Scopus, Web of Science, IEEE, medRxiv, arXiv, and Google Scholar were searched using specifi...

Artificial intelligence-assisted quantification and assessment of whole slide images for pediatric kidney disease diagnosis.

Bioinformatics (Oxford, England)
MOTIVATION: Pediatric kidney disease is a widespread, progressive condition that severely impacts growth and development of children. Chronic kidney disease is often more insidious in children than in adults, usually requiring a renal biopsy for diag...

Impact of AI Decision Support on Clinical Experts' Radiographic Interpretation of Adamantinomatous Craniopharyngioma.

AMIA ... Annual Symposium proceedings. AMIA Symposium
This research explores the integration of Artificial Intelligence (AI) into clinical decision-making in pediatric brain tumor care, specifically Adamantinomatous Craniopharyngioma (ACP). We present a user-centered design approach to introducing AI to...

The Impact of Artificial Intelligence on Quality of Life for Deaf and Hard of Hearing Students.

American annals of the deaf
This research study synthesizes research on applications of artificial intelligence (AI) to transform and improve quality of life for deaf and hard of hearing students. Twenty studies were analyzed, spanning domains including AI-enabled captioning, i...