AIMC Topic: Child

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How Artificial Intelligence, Virtual Reality, and Other Digital Technologies Are Changing the Field of Pediatric Neurogastroenterology.

Gastroenterology clinics of North America
Digital technology development is accelerating, with extended reality, artificial intelligence, and methods for information sharing leading the charge in broad medical specialties including pediatric neurogastroenterology. This rapid advancement must...

Artificial intelligence for the diagnosis of pediatric appendicitis: A systematic review.

The American journal of emergency medicine
BACKGROUND: While acute appendicitis is the most frequent surgical emergency in children, its diagnosis remains complex. Artificial intelligence (AI) and machine learning (ML) tools have been employed to improve the accuracy of various diagnoses, inc...

A multimodal machine learning algorithm improved diagnostic accuracy for otitis media in a school aged Aboriginal population.

Journal of biomedical informatics
OBJECTIVE: Otitis Media (OM) - ear infection - can lead to hearing loss and associated developmental delay. There are several subgroups of OM which can be difficult to diagnose accurately, even for experienced clinicians. AI and machine learning algo...

Interpretable machine learning approaches for children's ADHD detection using clinical assessment data: an online web application deployment.

BMC psychiatry
BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a prevalent mental disorder characterized by hyperactivity, impulsivity, and inattention. This study aims to develop a verifiable and interpretable machine learning model to identify ADHD...

An explainable and accurate transformer-based deep learning model for wheeze classification utilizing real-world pediatric data.

Scientific reports
Auscultation is a method that involves listening to sounds from the patient's body, mainly using a stethoscope, to diagnose diseases. The stethoscope allows for non-invasive, real-time diagnosis, and it is ideal for diagnosing respiratory diseases an...

Advancing Emotionally Aware Child-Robot Interaction with Biophysical Data and Insight-Driven Affective Computing.

Sensors (Basel, Switzerland)
This paper investigates the integration of affective computing techniques using biophysical data to advance emotionally aware machines and enhance child-robot interaction (CRI). By leveraging interdisciplinary insights from neuroscience, psychology, ...

Deep learning-assisted screening and diagnosis of scoliosis: segmentation of bare-back images via an attention-enhanced convolutional neural network.

Journal of orthopaedic surgery and research
BACKGROUND: Traditional diagnostic tools for scoliosis screening necessitate a substantial number of specialized personnel and equipment, leading to inconvenience that can result in missed opportunities for early diagnosis and optimal treatment. We h...

Automated pediatric TMJ articular disk identification and displacement classification in MRI with machine learning.

Journal of dentistry
OBJECTIVE: To evaluate the performance of an automated two-step model interpreting pediatric temporomandibular joint (TMJ) magnetic resonance imaging (MRI) using artificial intelligence (AI). Using deep learning techniques, the model first automatica...

Tailoring ventilation and respiratory management in pediatric critical care: optimizing care with precision medicine.

Current opinion in pediatrics
PURPOSE OF REVIEW: Critically ill children admitted to the intensive care unit frequently need respiratory care to support the lung function. Mechanical ventilation is a complex field with multiples parameters to set. The development of precision med...