AIMC Topic: Child

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Classification of COVID-19 by Compressed Chest CT Image through Deep Learning on a Large Patients Cohort.

Interdisciplinary sciences, computational life sciences
Corona Virus Disease (COVID-19) has spread globally quickly, and has resulted in a large number of causalities and medical resources insufficiency in many countries. Reverse-transcriptase polymerase chain reaction (RT-PCR) testing is adopted as biops...

Improving burn depth assessment for pediatric scalds by AI based on semantic segmentation of polarized light photography images.

Burns : journal of the International Society for Burn Injuries
This paper illustrates the efficacy of an artificial intelligence (AI) (a convolutional neural network, based on the U-Net), for the burn-depth assessment using semantic segmentation of polarized high-performance light camera images of burn wounds. T...

Use of artificial intelligence on Electroencephalogram (EEG) waveforms to predict failure in early school grades in children from a rural cohort in Pakistan.

PloS one
Universal primary education is critical for individual academic growth and overall adult productivity of nations. Estimates indicate that 25% of 59 million primary age out of school children drop out and early grade failure is one of the factors. An ...

Forecasting hand-foot-and-mouth disease cases using wavelet-based SARIMA-NNAR hybrid model.

PloS one
BACKGROUND: Hand-foot-and-mouth disease_(HFMD) is one of the most typical diseases in children that is associated with high morbidity. Reliable forecasting is crucial for prevention and control. Recently, hybrid models have become popular, and wavele...

Robotic lower extremity exoskeleton use in a non-ambulatory child with cerebral palsy: a case study.

Disability and rehabilitation. Assistive technology
PURPOSE: With few treatment options available for non-ambulatory children with cerebral palsy (CP), a robotic lower extremity gait trainer may provide a non-invasive addition to conventional treatment options. This case study investigates the usage a...

Classification of paediatric brain tumours by diffusion weighted imaging and machine learning.

Scientific reports
To determine if apparent diffusion coefficients (ADC) can discriminate between posterior fossa brain tumours on a multicentre basis. A total of 124 paediatric patients with posterior fossa tumours (including 55 Medulloblastomas, 36 Pilocytic Astrocyt...

Development and Validation of a Prediction Rule for Growth Hormone Deficiency Without Need for Pharmacological Stimulation Tests in Children With Risk Factors.

Frontiers in endocrinology
INTRODUCTION: Practice guidelines cannot recommend establishing a diagnosis of growth hormone deficiency (GHD) without performing growth hormone stimulation tests (GHST) in children with risk factors, due to the lack of sufficient evidence.

Artificial intelligence enables whole-body positron emission tomography scans with minimal radiation exposure.

European journal of nuclear medicine and molecular imaging
PURPOSE: To generate diagnostic F-FDG PET images of pediatric cancer patients from ultra-low-dose F-FDG PET input images, using a novel artificial intelligence (AI) algorithm.

An algorithm for using deep learning convolutional neural networks with three dimensional depth sensor imaging in scoliosis detection.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Timely intervention in growing individuals, such as brace treatment, relies on early detection of adolescent idiopathic scoliosis (AIS). To this end, several screening methods have been implemented. However, these methods have lim...