Pediatrics

Machine learning-based classification of petrofacies in fine laminated limestones.

Characterization and development of hydrocarbon reservoirs depends on the classification of litholog...

A complex fuzzy decision model for analysing the post-pandemic immuno-sustainability.

The post-effects of the COronaVIrus Disease (COVID-19) vary depending on socioeconomic and biologica...

Quantifying dysmorphologies of the neurocranium using artificial neural networks.

BACKGROUND: Craniosynostosis, a congenital condition characterized by the premature fusion of crania...

Machine Learning-Based Prediction of Suicidal Thinking in Adolescents by Derivation and Validation in 3 Independent Worldwide Cohorts: Algorithm Development and Validation Study.

BACKGROUND: Suicide is the second-leading cause of death among adolescents and is associated with cl...

Using machine learning algorithms and techniques for defining the impact of affective temperament types, content search and activities on the internet on the development of problematic internet use in adolescents' population.

BACKGROUND: By using algorithms and Machine Learning - ML techniques, the aim of this research was t...

Innovative AI methods for monitoring front-of-package information: A case study on infant foods.

Front-of-package (FOP) is one of the most direct communication channels connecting manufacturers and...

Editorial Comment: Usefulness of a Deep Learning Model for Pediatric Abdominal Organ Segmentation.

Predicting severe intraventricular hemorrhage or early death using machine learning algorithms in VLBWI of the Korean Neonatal Network Database.

Severe intraventricular hemorrhage (IVH) in premature infants can lead to serious neurological compl...

An Exaggeration? Reality?: Can ChatGPT Be Used in Neonatal Nursing?

Artificial intelligence (AI) represents a system endowed with the ability to derive meaningful infer...

Machine Learning Quantification of Pulmonary Regurgitation Fraction from Echocardiography.

Assessment of pulmonary regurgitation (PR) guides treatment for patients with congenital heart disea...

A prospective cohort-based artificial intelligence evaluation system for the protective efficacy and immune response of SARS-CoV-2 inactivated vaccines.

BACKGROUND: Novel coronaviruses constitute a significant health threat, prompting the adoption of va...

Machine Learning to Predict Outcomes of Fetal Cardiac Disease: A Pilot Study.

Prediction of outcomes following a prenatal diagnosis of congenital heart disease (CHD) is challengi...

Artificial Intelligence in the Future Landscape of Pediatric Neuroradiology: Opportunities and Challenges.

This paper will review how artificial intelligence (AI) will play an increasingly important role in ...

Machine learning models for abstract screening task - A systematic literature review application for health economics and outcome research.

OBJECTIVE: Systematic literature reviews (SLRs) are critical for life-science research. However, the...

Multimodal deep learning-based drought monitoring research for winter wheat during critical growth stages.

Wheat is a major grain crop in China, accounting for one-fifth of the national grain production. Dro...

Dynamic multilayer growth: Parallel vs. sequential approaches.

The decision of when to add a new hidden unit or layer is a fundamental challenge for constructive a...

Establishment and Verification of an Artificial Intelligence Prediction Model for Children With Sepsis.

BACKGROUND: Early identification of high-risk groups of children with sepsis is beneficial to reduce...

The Saudi Community View of the Use of Artificial Intelligence in Health Care.

OBJECTIVES: Artificial intelligence (AI) holds the promise to revolutionize the field of medicine an...

Application of machine learning approaches for predicting hemophilia A severity.

BACKGROUND: Hemophilia A (HA) is an X-linked congenital bleeding disorder, which leads to deficiency...

GNN-based structural information to improve DNN-based basal ganglia segmentation in children following early brain lesion.

Analyzing the basal ganglia following an early brain lesion is crucial due to their noteworthy role ...

Predicting humoral responses to primary and booster SARS-CoV-2 mRNA vaccination in people living with HIV: a machine learning approach.

BACKGROUND: SARS-CoV-2 mRNA vaccines are highly immunogenic in people living with HIV (PLWH) on effe...