Pediatrics

Latest AI and machine learning research in pediatrics for healthcare professionals.

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COVID-19 vaccinations and their side effects: a scoping systematic review.

The COVID-19 virus has impacted people worldwide, causing significant changes in their lifestyles. ...

Machine-learning-based evaluation of the usefulness of lactate for predicting neonatal mortality in preterm infants.

BACKGROUND: Unlike in adult and pediatric patients, the usefulness of lactate in preterm infants has...

Large-scale deep learning identifies the antiviral potential of PKI-179 and MTI-31 against coronaviruses.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to the global pandemic of Coron...

The Development and Application of KinomePro-DL: A Deep Learning Based Online Small Molecule Kinome Selectivity Profiling Prediction Platform.

Characterizing the kinome selectivity profiles of kinase inhibitors is essential in the early stages...

Predicting Outcomes of Preterm Neonates Post Intraventricular Hemorrhage.

Intraventricular hemorrhage (IVH) in preterm neonates presents a high risk for developing posthemorr...

[How well does artificial intelligence detect fractures in the cervical spine on CT?].

OBJECTIVE: To compare diagnostic accuracy of artificial intelligence (AI) for cervical spine (C-spin...

Deep learning for blood glucose level prediction: How well do models generalize across different data sets?

Deep learning-based models for predicting blood glucose levels in diabetic patients can facilitate p...

A machine learning-based electronic nose for detecting neonatal sepsis: Analysis of volatile organic compound biomarkers in fecal samples.

BACKGROUND: Neonatal sepsis is a global health threat, contributing to high morbidity and mortality ...

Comparative evaluation of interpretation methods in surface-based age prediction for neonates.

Significant changes in brain morphology occur during the third trimester of gestation. The capabilit...

Robust identification key predictors of short- and long-term weight status in children and adolescents by machine learning.

BACKGROUND: Early identification of high-risk individuals for weight problems in children and adoles...

Deep learning for rapid analysis of cell divisions in vivo during epithelial morphogenesis and repair.

Cell division is fundamental to all healthy tissue growth, as well as being rate-limiting in the tis...

Radiation dose reduction in pediatric computed tomography (CT) using deep convolutional neural network denoising.

AIM: We evaluated the quality of noncontrast chest computed tomography (CT) for pediatric patients a...

Chatbots in Limb Lengthening and Reconstruction Surgery: How Accurate Are the Responses?

BACKGROUND: Artificial intelligence-based language model chatbots are being increasingly used as a q...

An integrated machine learning model enhances delayed graft function prediction in pediatric renal transplantation from deceased donors.

BACKGROUND: Kidney transplantation is the optimal renal replacement therapy for children with end-st...

Prediction of preterm birth in multiparous women using logistic regression and machine learning approaches.

To predict preterm birth (PTB) in multiparous women, comparing machine learning approaches with trad...

The Emerging Role of Artificial Intelligence and Automated Platforms for the Assessment of Penile Curvature: A Scoping Review.

PURPOSE OF THE REVIEW: The estimation of penile curvature is an essential component in the assessmen...

Children Are Not Small Adults: Addressing Limited Generalizability of an Adult Deep Learning CT Organ Segmentation Model to the Pediatric Population.

Deep learning (DL) tools developed on adult data sets may not generalize well to pediatric patients,...

Development and evaluation of a model to identify publications on the clinical impact of pharmacist interventions.

BACKGROUND: Pharmacists are increasingly involved in patient care. Pharmacy practice research helps ...

Machine learning-based early prediction of growth and morphological traits at yearling age in pure and hybrid goat offspring.

The purpose of this study was to evaluate the performance of various prediction models in estimating...

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