AIMC Topic: Child

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Assessment of Facial Morphologic Features in Patients With Congenital Adrenal Hyperplasia Using Deep Learning.

JAMA network open
IMPORTANCE: Congenital adrenal hyperplasia (CAH) is the most common primary adrenal insufficiency in children, involving excess androgens secondary to disrupted steroidogenesis as early as the seventh gestational week of life. Although structural bra...

Sleep stage classification for child patients using DeConvolutional Neural Network.

Artificial intelligence in medicine
Studies from the literature show that the prevalence of sleep disorder in children is far higher than that in adults. Although much research effort has been made on sleep stage classification for adults, children have significantly different characte...

A robot that counts like a child: a developmental model of counting and pointing.

Psychological research
In this paper, a novel neuro-robotics model capable of counting real items is introduced. The model allows us to investigate the interaction between embodiment and numerical cognition. This is composed of a deep neural network capable of image proces...

Prediction of Cranial Radiotherapy Treatment in Pediatric Acute Lymphoblastic Leukemia Patients Using Machine Learning: A Case Study at MAHAK Hospital.

Asian Pacific journal of cancer prevention : APJCP
BACKGROUND: Acute Lymphoblastic Leukemia (ALL) is the most common blood disease in children and is responsible for the most deaths amongst children. Due to major improvements in the treatment protocols in the 50-years period, the survivability of thi...

Machine learning model demonstrates stunting at birth and systemic inflammatory biomarkers as predictors of subsequent infant growth - a four-year prospective study.

BMC pediatrics
BACKGROUND: Stunting affects up to one-third of the children in low-to-middle income countries (LMICs) and has been correlated with decline in cognitive capacity and vaccine immunogenicity. Early identification of infants at risk is critical for earl...

Accurate detection of cerebellar smooth pursuit eye movement abnormalities via mobile phone video and machine learning.

Scientific reports
Eye movements are disrupted in many neurodegenerative diseases and are frequent and early features in conditions affecting the cerebellum. Characterizing eye movements is important for diagnosis and may be useful for tracking disease progression and ...

Trends in robotic surgery utilization across tertiary children's hospitals in the United States.

Surgical endoscopy
BACKGROUND: A growing number of tertiary children's hospitals are utilizing robotic surgical technology. We sought to characterize national trends in pediatric surgical robotic case utilization and related drivers.

Traditional and New Methods of Bone Age Assessment-An Overview.

Journal of clinical research in pediatric endocrinology
Bone age is one of biological indicators of maturity used in clinical practice and it is a very important parameter of a child’s assessment, especially in paediatric endocrinology. The most widely used method of bone age assessment is by performing a...

Decision-making in pediatric blunt solid organ injury: A deep learning approach to predict massive transfusion, need for operative management, and mortality risk.

Journal of pediatric surgery
BACKGROUND: The principal triggers for intervention in the setting of pediatric blunt solid organ injury (BSOI) are declining hemoglobin values and hemodynamic instability. The clinical management of BSOI is, however, complex. We therefore hypothesiz...

Automated identification of postural control for children with autism spectrum disorder using a machine learning approach.

Journal of biomechanics
It is unclear whether postural sway characteristics could be used as diagnostic biomarkers for autism spectrum disorder (ASD). The purpose of this study was to develop and validate an automated identification of postural control patterns in children ...