AIMC Topic: Child

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Demographic, Clinical, and Allergic Characteristics of Children with Eosinophilic Esophagitis in Isfahan, Iran.

Iranian journal of allergy, asthma, and immunology
Eosinophilic esophagitis (EoE) is a chronic immune-mediated disease isolated to the esophagus Food allergy is thought to play an important role in the pathophysiology of EOE. The aim of this study is to evaluate demographic features and sensitivity o...

Toward a motor signature in autism: Studies from human-machine interaction.

L'Encephale
BACKGROUND: Autism spectrum disorder (ASD) is a heterogeneous group of neurodevelopmental disorders which core symptoms are impairments in socio-communication and repetitive symptoms and stereotypies. Although not cardinal symptoms per se, motor impa...

A Machine Learning Approach to Predicting Need for Hospitalization for Pediatric Asthma Exacerbation at the Time of Emergency Department Triage.

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
OBJECTIVES: Pediatric asthma is a leading cause of emergency department (ED) utilization and hospitalization. Earlier identification of need for hospital-level care could triage patients more efficiently to high- or low-resource ED tracks. Existing t...

Dynamic changes in specific anti-L-asparaginase antibodies generation during acute lymphoblastic leukemia treatment.

Pharmacological reports : PR
BACKGROUND: L-asparaginase (L-asp) remains one of the key components of acute lymphoblastic leukemia therapy. Immune reactions to the drug are associated with its diminished activity. The aim of the study was to determine the level of IgM, IgG and Ig...

The RSNA Pediatric Bone Age Machine Learning Challenge.

Radiology
Purpose The Radiological Society of North America (RSNA) Pediatric Bone Age Machine Learning Challenge was created to show an application of machine learning (ML) and artificial intelligence (AI) in medical imaging, promote collaboration to catalyze ...

Mobile detection of autism through machine learning on home video: A development and prospective validation study.

PLoS medicine
BACKGROUND: The standard approaches to diagnosing autism spectrum disorder (ASD) evaluate between 20 and 100 behaviors and take several hours to complete. This has in part contributed to long wait times for a diagnosis and subsequent delays in access...

Ossification area localization in pediatric hand radiographs using deep neural networks for object detection.

PloS one
BACKGROUND: Detection of ossification areas of hand bones in X-ray images is an important task, e.g. as a preprocessing step in automated bone age estimation. Deep neural networks have emerged recently as de facto standard detection methods, but thei...

Machine learning of brain gray matter differentiates sex in a large forensic sample.

Human brain mapping
Differences between males and females have been extensively documented in biological, psychological, and behavioral domains. Among these, sex differences in the rate and typology of antisocial behavior remains one of the most conspicuous and enduring...

Machine learning algorithms for activity recognition in ambulant children and adolescents with cerebral palsy.

Journal of neuroengineering and rehabilitation
BACKGROUND: Cerebral palsy (CP) is the most common physical disability among children (2.5 to 3.6 cases per 1000 live births). Inadequate physical activity (PA) is a major problem effecting the health and well-being of children with CP. Practical, ye...

Machine learning to identify pairwise interactions between specific IgE antibodies and their association with asthma: A cross-sectional analysis within a population-based birth cohort.

PLoS medicine
BACKGROUND: The relationship between allergic sensitisation and asthma is complex; the data about the strength of this association are conflicting. We propose that the discrepancies arise in part because allergic sensitisation may not be a single ent...