AIMC Topic: Child

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The study of the differences between low-functioning autistic children and typically developing children in the processing of the own-race and other-race faces by the machine learning approach.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
OBJECTIVE: Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder which affects the developmental trajectory in several behavioral domains, including impairments of social communication and stereotyped behavior. Unlike typicall...

THEIA™ development, and testing of artificial intelligence-based primary triage of diabetic retinopathy screening images in New Zealand.

Diabetic medicine : a journal of the British Diabetic Association
AIM: To develop and evaluate an artificial intelligence triage system with high sensitivity for detecting referable diabetic retinopathy and maculopathy, while maintaining high specificity for non-referable disease, for clinical implementation within...

Robot-assisted laparoscopic extravesical versus conventional laparoscopic extravesical ureteric reimplantation for pediatric primary vesicoureteric reflux: a systematic review and meta-analysis.

Pediatric surgery international
To perform a systematic review and meta-analysis comparing the outcomes of robotic-assisted laparoscopic extravesical ureteric reimplantation (RALUR) with conventional laparoscopic extravesical ureteric reimplantation (LEVUR) for primary vesicoureter...

Deep Learning Model for the Automated Detection and Histopathological Prediction of Meningioma.

Neuroinformatics
The volumetric assessment and accurate grading of meningiomas before surgery are highly relevant for therapy planning and prognosis prediction. This study was to design a deep learning algorithm and evaluate the performance in detecting meningioma le...

Deep learning-based synthetic CT generation for paediatric brain MR-only photon and proton radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: To enable accurate magnetic resonance imaging (MRI)-based dose calculations, synthetic computed tomography (sCT) images need to be generated. We aim at assessing the feasibility of dose calculations from MRI acquired with a he...

Artificial intelligence in detection and segmentation of internal auditory canal and its nerves using deep learning techniques.

International journal of computer assisted radiology and surgery
PURPOSE: Artificial intelligence (AI) in medical imaging is a burgeoning topic that involves the interpretation of complex image structures. The recent advancements in deep learning techniques increase the computational powers to extract vital featur...

Artificial intelligence in paediatric radiology: Future opportunities.

The British journal of radiology
Artificial intelligence (AI) has received widespread and growing interest in healthcare, as a method to save time, cost and improve efficiencies. The high-performance statistics and diagnostic accuracies reported by using AI algorithms (with respect ...

A multi-task, multi-stage deep transfer learning model for early prediction of neurodevelopment in very preterm infants.

Scientific reports
Survivors following very premature birth (i.e., ≤ 32 weeks gestational age) remain at high risk for neurodevelopmental impairments. Recent advances in deep learning techniques have made it possible to aid the early diagnosis and prognosis of neurodev...

New Machine Learning Approach for Detection of Injury Risk Factors in Young Team Sport Athletes.

International journal of sports medicine
The purpose of this article is to present how predictive machine learning methods can be utilized for detecting sport injury risk factors in a data-driven manner. The approach can be used for finding new hypotheses for risk factors and confirming the...

Artificial Intelligence Predictive Analytics in the Management of Outpatient MRI Appointment No-Shows.

AJR. American journal of roentgenology
Outpatient appointment no-shows are a common problem. Artificial intelligence predictive analytics can potentially facilitate targeted interventions to improve efficiency. We describe a quality improvement project that uses machine learning techniqu...