AIMC Topic: Child

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Assessment of Agreement Between Human Ratings and Lexicon-Based Sentiment Ratings of Open-Ended Responses on a Behavioral Rating Scale.

Assessment
To date, there is a paucity of research conducting natural language processing (NLP) on the open-ended responses of behavior rating scales. Using three NLP lexicons for sentiment analysis of the open-ended responses of the Behavior Assessment System ...

Using deep learning and natural language processing models to detect child physical abuse.

Journal of pediatric surgery
BACKGROUND: The recognition of child physical abuse can be challenging and often requires a multidisciplinary assessment. Deep learning models, based on clinical characteristics, laboratory studies, and imaging findings, were developed to facilitate ...

Robot-assisted stereoelectroencephalography electrode placement in twenty-three pediatric patients: a high-resolution analysis of individual lead placement time and accuracy at a single institution.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
PURPOSE: We describe a detailed evaluation of predictors associated with individual lead placement efficiency and accuracy for 261 stereoelectroencephalography (sEEG) electrodes placed for epilepsy monitoring in twenty-three children at our instituti...

Integrating human services and criminal justice data with claims data to predict risk of opioid overdose among Medicaid beneficiaries: A machine-learning approach.

PloS one
Health system data incompletely capture the social risk factors for drug overdose. This study aimed to improve the accuracy of a machine-learning algorithm to predict opioid overdose risk by integrating human services and criminal justice data with h...

Prediction of baseline expressive and receptive language function in children with focal epilepsy using diffusion tractography-based deep learning network.

Epilepsy & behavior : E&B
PURPOSE: Focal epilepsy is a risk factor for language impairment in children. We investigated whether the current state-of-the-art deep learning network on diffusion tractography connectome can accurately predict expressive and receptive language sco...

Overground Robot-Assisted Gait Training for Pediatric Cerebral Palsy.

Sensors (Basel, Switzerland)
The untethered exoskeletal robot provides patients with the freest and realistic walking experience by assisting them based on their intended movement. However, few previous studies have reported the effect of robot-assisted gait training (RAGT) usin...

Age estimates from brain magnetic resonance images of children younger than two years of age using deep learning.

Magnetic resonance imaging
The accuracy of brain age estimates from magnetic resonance (MR) images has improved with the advent of deep learning artificial intelligence (AI) models. However, most previous studies on predicting age emphasized aging from childhood to adulthood a...

Using Machine Learning to Unravel the Value of Radiographic Features for the Classification of Bone Tumors.

BioMed research international
OBJECTIVES: To build and validate random forest (RF) models for the classification of bone tumors based on the conventional radiographic features of the lesion and patients' clinical characteristics, and identify the most essential features for the c...