AIMC Topic: Child

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Effect of pedestrian physique differences on head injury prediction in car-to-pedestrian accidents using deep learning.

Traffic injury prevention
OBJECTIVE: The aim of this study is to identify the effects of pedestrian physique differences on head injury prediction in car-to-pedestrian accidents via deep learning.

Detecting Phase-Synchrony Connectivity Anomalies in EEG Signals. Application to Dyslexia Diagnosis.

Sensors (Basel, Switzerland)
Objective Dyslexia diagnosis is a challenging task, since traditional diagnosis methods are not based on biological markers but on behavioural tests. Although dyslexia diagnosis has been addressed by these tests in clinical practice, it is difficult ...

One-dimensional convolutional neural network and hybrid deep-learning paradigm for classification of specific language impaired children using their speech.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Screening children for communicational disorders such as specific language impairment (SLI) is always challenging as it requires clinicians to follow a series of steps to evaluate the subjects. Artificial intelligence and co...

Deep Learning Algorithms-Based CT Images in Glucocorticoid Therapy in Asthma Children with Small Airway Obstruction.

Journal of healthcare engineering
CT image information data under deep learning algorithms was adopted to evaluate small airway function and analyze the clinical efficacy of different glucocorticoid administration ways in asthmatic children with small airway obstruction. The Res-NET ...

The augmented radiologist: artificial intelligence in the practice of radiology.

Pediatric radiology
In medicine, particularly in radiology, there are great expectations in artificial intelligence (AI), which can "see" more than human radiologists in regard to, for example, tumor size, shape, morphology, texture and kinetics - thus enabling better c...

Predicting obesity and smoking using medication data: A machine-learning approach.

Pharmacoepidemiology and drug safety
PURPOSE: Administrative health datasets are widely used in public health research but often lack information about common confounders. We aimed to develop and validate machine learning (ML)-based models using medication data from Australia's Pharmace...

Limited generalizability of deep learning algorithm for pediatric pneumonia classification on external data.

Emergency radiology
PURPOSE: (1) Develop a deep learning system (DLS) to identify pneumonia in pediatric chest radiographs, and (2) evaluate its generalizability by comparing its performance on internal versus external test datasets.

Advanced Kidney Volume Measurement Method Using Ultrasonography with Artificial Intelligence-Based Hybrid Learning in Children.

Sensors (Basel, Switzerland)
In this study, we aimed to develop a new automated method for kidney volume measurement in children using ultrasonography (US) with image pre-processing and hybrid learning and to formulate an equation to calculate the expected kidney volume. The vol...

Walking-induced exposure of biological particles simulated by a children robot with different shoes on public floors.

Environment international
Inhalation exposure to the resuspended biological particles from public places can cause adverse effects on human health. In this work, carpet dust samples were first collected from twenty example conference and hotel rooms by a vacuum cleaner. A bip...

Artificial intelligence in paediatric radiology: international survey of health care professionals' opinions.

Pediatric radiology
BACKGROUND: The nature of paediatric radiology work poses several challenges for developing and implementing artificial intelligence (AI) tools, but opinions of those working in the field are currently unknown.