Pediatrics

Early detection of late-onset neonatal sepsis from noninvasive biosignals using deep learning: A multicenter prospective development and validation study.

BACKGROUND: Neonatal sepsis is responsible for significant morbidity and mortality worldwide. Its accurate and timely diagnosis is hindered by vague symptoms and the urgent necessity for early antibiotic intervention. The gold standard for diagnosing the condition is the identification of a pathogenic organism from normally sterile sites via laboratory testing. However, this method is resource-int...

Machine Learning-Based Prediction of Pediatric Ulcerative Colitis Treatment Response Using Diagnostic Histopathology.

Potential merits and flaws of large language models in epilepsy care: A critical review.

The current pace of development and applications of large language models (LLMs) is unprecedented and will impact future medical care significantly. I...

Deep learning in water protection of resources, environment, and ecology: achievement and challenges.

The breathtaking economic development put a heavy toll on ecology, especially on water pollution. Efficient water resource management has a long-term ...

Deep-Learning-Based Analysis Reveals a Social Behavior Deficit in Mice Exposed Prenatally to Nicotine.

Cigarette smoking during pregnancy is known to be associated with the incidence of attention-deficit/hyperactive disorder (ADHD). Recent developments ...

Automatic dental age calculation from panoramic radiographs using deep learning: a two-stage approach with object detection and image classification.

BACKGROUND: Dental age is crucial for treatment planning in pediatric and orthodontic dentistry. Dental age calculation methods can be categorized int...

Artificial Intelligence in the Diagnosis and Management of Appendicitis in Pediatric Departments: A Systematic Review.

INTRODUCTION:  Artificial intelligence (AI) is a growing field in medical research that could potentially help in the challenging diagnosis of acute a...

Large Language Models in Medicine: The Potentials and Pitfalls : A Narrative Review.

Large language models (LLMs) are artificial intelligence models trained on vast text data to generate humanlike outputs. They have been applied to var...

Application of STREAM-URO and APPRAISE-AI reporting standards for artificial intelligence studies in pediatric urology: A case example with pediatric hydronephrosis.

INTRODUCTION: Artificial intelligence (AI) and machine learning (ML) in pediatric urology is gaining increased popularity and credibility. However, th...

Artificial intelligence-based model for dose prediction of sertraline in adolescents: a real-world study.

BACKGROUND: Variability exists in sertraline pharmacokinetic parameters in individuals, especially obvious in adolescents. We aimed to establish an in...

Effect of Light-Emitting Grid Panel on Indoor Aquaculture for Measuring Fish Growth.

This study is related to Smart Aqua Farm, which combines artificial intelligence (AI) and Internet of things (IoT) technology. This study aimed to mon...

The association of serum irisin with anthropometric, metabolic, and bone parameters in obese children and adolescents.

BACKGROUND: Irisin is an adipomyokine secreted by muscle and adipose cells, and it plays a role in glucose, fat, and bone metabolism. This study aimed...

Exploring new horizons: Emerging therapeutic strategies for pediatric stroke.

Pediatric stroke presents unique challenges, and optimizing treatment strategies is essential for improving outcomes in this vulnerable population. Th...

Rule-based deep learning method for prognosis of neonatal hypoxic-ischemic encephalopathy by using susceptibility weighted image analysis.

OBJECTIVE: Susceptibility weighted imaging (SWI) of neonatal hypoxic-ischemic brain injury can provide assistance in the prognosis of neonatal hypoxic...

Pediatric Pulmonary Function Assessment Using Artificial Intelligence with Cough Sounds.

Deep Learning Auto-Segmentation Network for Pediatric Computed Tomography Data Sets: Can We Extrapolate From Adults?

PURPOSE: Artificial intelligence (AI)-based auto-segmentation models hold promise for enhanced efficiency and consistency in organ contouring for adap...

The Reporting Quality of Machine Learning Studies on Pediatric Diabetes Mellitus: Systematic Review.

BACKGROUND: Diabetes mellitus (DM) is a major health concern among children with the widespread adoption of advanced technologies. However, concerns a...

Evaluation of robot-assisted laparoscopic versus conventional laparoscopic hiatal hernia repair in children.

Laparoscopic approach is the gold standard for repairing hiatal hernia (HH). Robotic technology is now widely accepted, but it is rarely used in child...

A CNN-based model to count the leaves of rosette plants (LC-Net).

Plant image analysis is a significant tool for plant phenotyping. Image analysis has been used to assess plant trails, forecast plant growth, and offe...

Solving olympiad geometry without human demonstrations.

Proving mathematical theorems at the olympiad level represents a notable milestone in human-level automated reasoning, owing to their reputed difficul...