AIMC Topic: Child
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A prediction model of pediatric bone density from plain spine radiographs using deep learning.
Scientific reports
Apr 15, 2025
Osteoporosis, a bone disease characterized by decreased bone mineral density (BMD) resulting in decreased mechanical strength and an increased fracture risk, remains poorly understood in children. Herein, we developed/validated a deep learning-based ...
A deep learning approach for blood glucose monitoring and hypoglycemia prediction in glycogen storage disease.
Scientific reports
Apr 15, 2025
Glycogen storage disease (GSD) is a group of rare inherited metabolic disorders characterized by abnormal glycogen storage and breakdown. These disorders are caused by mutations in G6PC1, which is essential for proper glucose storage and metabolism. ...
Machine learning models for improving the diagnosing efficiency of skeletal class I and III in German orthodontic patients.
Scientific reports
Apr 13, 2025
The precise and efficient diagnosis of an individual's skeletal class is necessary in orthodontics to ensure correct and stable treatment planning. However, it is difficult to efficiently determine the true skeletal class due to several correlations ...
A diagnosis and prediction algorithm for juvenile myoclonic epilepsy based on clinical and quantitative EEG features.
Seizure
Apr 12, 2025
OBJECTIVE: To develop an objective ensemble machine learning model combining clinical features and quantitative EEG metrics (phase locking value [PLV] and multiscale sample entropy [MSE]) to support accurate diagnosis of juvenile myoclonic epilepsy (...
Explainable AI for enhanced accuracy in malaria diagnosis using ensemble machine learning models.
BMC medical informatics and decision making
Apr 11, 2025
BACKGROUND: Malaria, an infectious disease caused by protozoan parasites belonging to the Plasmodium genus, remains a significant public health challenge, with African regions bearing the heaviest burden. Machine learning techniques have shown great ...
Utilizing machine learning and geographic analysis to improve Post-crash traffic injury management and emergency response systems.
International journal of injury control and safety promotion
Apr 11, 2025
Traffic injuries are a major public health concern globally. This study uses machine learning (ML) and geographic analysis to analyse road traffic fatalities and improve traffic safety in Nakhon Ratchasima Province, Thailand. Data on road traffic fat...
Children on wheels: Identifying crash determinants using cluster correspondence analysis.
Accident; analysis and prevention
Apr 10, 2025
Child bicyclists (14 years old and younger) are among the most vulnerable road users, facing significant risks of crashes that often result in severe injuries or fatalities. This study aims to identify key factors influencing child bicyclist crashes ...
Exploring cortical excitability in children with cerebral palsy through lower limb robot training based on MI-BCI.
Scientific reports
Apr 10, 2025
This study aims to compare brain activity differences under the motor imagery-brain-computer interface (MI-BCI), motor imagery (MI), and resting (REST) paradigms through EEG microstate and functional connectivity (FC) analysis, providing a theoretica...
Prediction of outpatient visits for allergic rhinitis using an artificial intelligence LSTM model - a study in Eastern China.
BMC public health
Apr 9, 2025
BACKGROUND: Allergic rhinitis is a common disease that can affect the health of patients and bring huge social and economic burdens. In this study, we developed a model to predict the incidence rate of allergic rhinitis so as to provide accurate info...
The potential of evaluating shape drawing using machine learning for predicting high autistic traits.
PloS one
Apr 9, 2025
BACKGROUND: Children with high autistic traits often exhibit deficits in drawing, an important skill for social adaptability. Machine learning is a powerful technique for learning predictive models from movement data, so drawing processes and product...
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