AIMC Topic: Child

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Prediction model of dental caries in 12-year-old children in Sichuan Province based on machine learning.

Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology
OBJECTIVES: The machine learning algorithm was used to construct a prediction model of children's dental caries to determine the risk factors of dental caries in children and put forward targeted measures and policy suggestions to improve children's ...

Predicting Antiseizure Medication Treatment in Children with Rare Tuberous Sclerosis Complex-Related Epilepsy Using Deep Learning.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Tuberous sclerosis complex disease is a rare, multisystem genetic disease, but appropriate drug treatment allows many pediatric patients to have positive outcomes. The purpose of this study was to predict the effectiveness of ...

Robotic Rehabilitation in Children.

Psychiatria Danubina
The robot assisted rehabilitation constitutes a recent therapeutic opportunity for the motor disorders in children with neurological disabilities. Robot-based devices are useful to promote improvements in sensorimotor and cognitive process. Robot-ass...

Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Development of electronic health records (EHR)-based machine learning models for pediatric inpatients is challenged by limited training data. Self-supervised learning using adult data may be a promising approach to creating robust pediatri...

Pilot study of machine learning in the task of distinguishing high and low-grade pediatric hydronephrosis on ultrasound.

Investigative and clinical urology
PURPOSE: Hydronephrosis is a common pediatric urological condition, characterized by dilation of the renal collecting system. Accurate identification of the severity of hydronephrosis is crucial in clinical management, as high-grade hydronephrosis ca...

Bone Age Assessment Using Artificial Intelligence in Korean Pediatric Population: A Comparison of Deep-Learning Models Trained With Healthy Chronological and Greulich-Pyle Ages as Labels.

Korean journal of radiology
OBJECTIVE: To develop a deep-learning-based bone age prediction model optimized for Korean children and adolescents and evaluate its feasibility by comparing it with a Greulich-Pyle-based deep-learning model.

Robot-assisted thoracoscopic surgery for mediastinal tumours in children: a single-centre retrospective study of 149 patients.

European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
OBJECTIVES: The purpose of this retrospective study was to summarize our experience in performing robot-assisted thoracoscopic surgery (RATS) for mediastinal tumours in children to investigate its safety and feasibility.

Bone Age Estimation and Prediction of Final Adult Height Using Deep Learning.

Yonsei medical journal
PURPOSE: The appropriate evaluation of height and accurate estimation of bone age are crucial for proper assessment of the growth status of a child. We developed a bone age estimation program using a deep learning algorithm and established a model to...