Pediatrics

Uses and limitations of artificial intelligence for oncology.

Modern artificial intelligence (AI) tools built on high-dimensional patient data are reshaping oncology care, helping to improve goal-concordant care, decrease cancer mortality rates, and increase workflow efficiency and scope of care. However, data-related concerns and human biases that seep into algorithms during development and post-deployment phases affect performance in real-world settings, l...

Machine learning-based analysis for prediction of surgical necrotizing enterocolitis in very low birth weight infants using perinatal factors: a nationwide cohort study.

Early prediction of surgical necrotizing enterocolitis (sNEC) in preterm infants is important. However, owing to the complexity of the disease, identifying infants with NEC at a high risk for surgical intervention is difficult. We developed a machine learning (ML) algorithm to predict sNEC using perinatal factors obtained from the national cohort registry of very low birth weight (VLBW) infants. D...

Explainable prediction of problematic smartphone use among South Korea's children and adolescents using a Machine learning approach.

BACKGROUND: Korea is known for its technological prowess, has the highest smartphone ownership rate in the world at 95%, and the smallest gap in smart...

Supervised representation learning based on various levels of pediatric radiographic views for transfer learning.

Transfer learning plays a pivotal role in addressing the paucity of data, expediting training processes, and enhancing model performance. Nonetheless,...

Calculated Medicine: Seven Decades of Accelerating Growth.

The field of Calculated Medicine has grown substantially over the last 7 decades. Comprised of objective, evidence-based medical decision tools, Calcu...

[Artificial intelligence in intensive care medicine].

The integration of artificial intelligence (AI) into intensive care medicine has made considerable progress in recent studies, particularly in the are...

Mapping cell-to-tissue graphs across human placenta histology whole slide images using deep learning with HAPPY.

Accurate placenta pathology assessment is essential for managing maternal and newborn health, but the placenta's heterogeneity and temporal variabilit...

Correlative Assessment of Machine Learning-Based Cobb Angle Measurements and Human-Based Measurements in Adolescent Idiopathic and Congenital Scoliosis.

Scoliosis is a complex spine deformity with direct functional and cosmetic impacts on the individual. The reference standard for assessing scoliosis ...

Artificial Intelligence in Hand Surgery - How Generative AI is Transforming the Hand Surgery Landscape.

Artificial intelligence (AI) has witnessed significant advancements, reshaping various industries, including healthcare. The introduction of ChatGPT b...

Determination of minimum inhibitory concentrations using machine-learning-assisted agar dilution.

UNLABELLED: Effective policy to address the global threat of antimicrobial resistance requires robust antimicrobial susceptibility data. Traditional m...

A motion-corrected deep-learning reconstruction framework for accelerating whole-heart magnetic resonance imaging in patients with congenital heart disease.

BACKGROUND: Cardiovascular magnetic resonance (CMR) is an important imaging modality for the assessment and management of adult patients with congenit...

Improving newborn screening in India: Disease gaps and quality control.

In India, newborn screening (NBS) is essential for detecting health problems in infants. Despite significant progress, significant gaps and challenges...

Dental age estimation: A comparative study of convolutional neural network and Demirjian's method.

The aim of this study is to compare a technique using Convolutional Neural Network (CNN) with the Demirjian's method for chronological age estimation ...

Statistical and machine learning analysis for the application of microbially induced carbonate precipitation as a physical barrier to control seawater intrusion.

Seawater intrusion in coastal aquifers is a significant problem that can be addressed through the construction of subsurface dams or physical cut-off ...

Screening/diagnosis of pediatric endocrine disorders through the artificial intelligence model in different language settings.

UNLABELLED: This study is aimed at examining the impact of ChatGPT on pediatric endocrine and metabolic conditions, particularly in the areas of scree...

Artificial intelligence to classify acquired intestinal injury in preterm neonates-a new perspective.

Enhancing pediatric pneumonia diagnosis through masked autoencoders.

Pneumonia, an inflammatory lung condition primarily triggered by bacteria, viruses, or fungi, presents distinctive challenges in pediatric cases due t...

Can an AI-carebot be filial? Reflections from Confucian ethics.

This article discusses the application of artificially intelligent robots within eldercare and explores a series of ethical considerations, including ...

Harnessing the Power of Generative AI for Clinical Summaries: Perspectives From Emergency Physicians.

STUDY OBJECTIVE: The workload of clinical documentation contributes to health care costs and professional burnout. The advent of generative artificial...

Gated cardiac CT in infants: What can we expect from deep learning image reconstruction algorithm?

BACKGROUND: ECG-gated cardiac CT is now widely used in infants with congenital heart disease (CHD). Deep Learning Image Reconstruction (DLIR) could im...