AIMC Topic: Child

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Retraining an Artificial Intelligence Algorithm to Calculate Left Ventricular Ejection Fraction in Pediatrics.

Journal of cardiothoracic and vascular anesthesia
OBJECTIVES: Identifying patients with low left ventricular ejection fraction (LVEF) and monitoring LVEF responses to treatment are important clinical goals. Can a deep-learning algorithm predict pediatric LVEF within clinically acceptable error?

Automated detection of acute appendicular skeletal fractures in pediatric patients using deep learning.

Skeletal radiology
OBJECTIVE: We aimed to perform an external validation of an existing commercial AI software program (BoneView™) for the detection of acute appendicular fractures in pediatric patients.

The effect of robotic rehabilitation on posture and trunk control in non-ambulatory cerebral palsy.

Assistive technology : the official journal of RESNA
The purpose of this study was to investigate the effects of a combined robot-assisted gait training (RAGT) with standard physiotherapy (PT) on trunk control and posture in non-ambulatory children with cerebral palsy (CP). This nonrandomized, controll...

Dynamic Mortality Risk Predictions for Children in ICUs: Development and Validation of Machine Learning Models.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies
OBJECTIVES: Assess a machine learning method of serially updated mortality risk.

Monitoring Approaches for a Pediatric Chronic Kidney Disease Machine Learning Model.

Applied clinical informatics
OBJECTIVE: The purpose of this study is to evaluate the ability of three metrics to monitor for a reduction in performance of a chronic kidney disease (CKD) model deployed at a pediatric hospital.

Using deep transfer learning to detect scoliosis and spondylolisthesis from x-ray images.

PloS one
Recent years have witnessed wider prevalence of vertebral column pathologies due to lifestyle changes, sedentary behaviors, or injuries. Spondylolisthesis and scoliosis are two of the most common ailments with an incidence of 5% and 3% in the United ...

Deciphering the blackbox of omics approaches and artificial intelligence in food waste transformation and mitigation.

International journal of food microbiology
It is necessary to stop the wastage of food during any stage of food chain to resolve the challenge of starvation, hunger and malnutrition in the world. Inception of modern techniques like omics (metagenomics, proteomics, transcriptomics, wasteomics,...

Explainable AI in Diagnosing and Anticipating Leukemia Using Transfer Learning Method.

Computational intelligence and neuroscience
White blood cells (WBCs) are blood cells that fight infections and diseases as a part of the immune system. They are also known as "defender cells." But the imbalance in the number of WBCs in the blood can be hazardous. Leukemia is the most common bl...

Pediatric chest radiograph interpretation: how far has artificial intelligence come? A systematic literature review.

Pediatric radiology
Most artificial intelligence (AI) studies have focused primarily on adult imaging, with less attention to the unique aspects of pediatric imaging. The objectives of this study were to (1) identify all publicly available pediatric datasets and determi...

Environmental and clinical data utility in pediatric asthma exacerbation risk prediction models.

BMC medical informatics and decision making
BACKGROUND: Asthma exacerbations are triggered by a variety of clinical and environmental factors, but their relative impacts on exacerbation risk are unclear. There is a critical need to develop methods to identify children at high-risk for future e...