Pediatrics

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.

OBJECTIVE: To develop a deep-learning-based bone age prediction model optimized for Korean children ...

Development of a New Korean Standard Bone Age Model: A Paradigm for AI-Powered Pediatric Imaging.

A multi-scale expression and regulation knowledge base for Escherichia coli.

Transcriptomic data is accumulating rapidly; thus, scalable methods for extracting knowledge from th...

[Review on ultrasonographic diagnosis of thyroid diseases based on deep learning].

In recent years, the incidence of thyroid diseases has increased significantly and ultrasound examin...

Plasma insulin-like growth factor-II (IGF-II) and IGF-II/IGF-I ratio in a chilean case of Doege-Potter Syndrome.

INTRODUCTION: Doege-Potter syndrome is a rare clinical entity characterized by recurrent hypoglycemi...

Maintaining High-Touch in High-Tech Digital Health Monitoring and Multi-Omics Prognostication: Ethical, Equity, and Societal Considerations in Precision Health for Palliative Care.

Advances in digital health, systems biology, environmental monitoring, and artificial intelligence (...

ExpertNet: A Deep Learning Approach to Combined Risk Modeling and Subtyping in Intensive Care Units.

Risk models play a crucial role in disease prevention, particularly in intensive care units (ICUs). ...

Investigating the Influence of Artificial Intelligence on Adolescent Health: An Urgent Call to Action.

Development of a Machine Learning-Based Prescriptive Tool to Address Racial Disparities in Access to Care After Penetrating Trauma.

IMPORTANCE: The use of artificial intelligence (AI) in clinical medicine risks perpetuating existing...

Development and Validation of a Kinematically Accurate Upper-Limb Exoskeleton Digital Twin for Stroke Rehabilitation.

Rehabilitation robotics combined with virtual reality using head-mounted displays enable naturalisti...

1D-Convolutional Neural Networks can Quantify Therapy Content of Children and Adolescents Walking in a Robot-Assisted Gait Trainer.

Therapy content, consisting of device parameter settings and therapy instructions, is crucial for an...

Pediatric Allergy and Immunology (PAI) is for polishing with artificial intelligence, but careful use.

How far has robot-assisted partial nephrectomy reached?

Nephron-sparing surgery is the standard treatment for small renal mass (SRM). Nephron-sparing surger...

A convolutional neural network-based decision support system for neonatal quiet sleep detection.

Sleep plays an important role in neonatal brain and physical development, making its detection and c...

SEINN: A deep learning algorithm for the stochastic epidemic model.

Stochastic modeling predicts various outcomes from stochasticity in the data, parameters and dynamic...

Technology and Tool Development for BACPAC: Qualitative and Quantitative Analysis of Accelerated Lumbar Spine MRI with Deep-Learning Based Image Reconstruction at 3T.

OBJECTIVES: To evaluate whether combining fast acquisitions with deep-learning reconstruction can pr...

Automatically Predicting Perceived Conversation Quality in a Pediatric Sample Enriched for Autism.

Social interaction quality ratings derived from short natural conversations can differentiate childr...

Bringing At-home Pediatric Sleep Apnea Testing Closer to Reality: A Multi-modal Transformer Approach.

Sleep apnea in children is a major health problem affecting one to five percent of children (in the ...

Validation of an artificial intelligence-based method to automate Cobb angle measurement on spinal radiographs of children with adolescent idiopathic scoliosis.

BACKGROUND: Accurately measuring the Cobb angle on radiographs is crucial for diagnosis and treatmen...

Predictive overfitting in immunological applications: Pitfalls and solutions.

Overfitting describes the phenomenon where a highly predictive model on the training data generalize...

Long-term SARS-CoV-2 neutralizing antibody level prediction using multimodal deep learning: A prospective cohort study on longitudinal data in Wuhan, China.

The ongoing epidemic of SARS-CoV-2 is taking a substantial financial and health toll on people world...