Pediatrics

Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design.

Peptides can bind challenging disease targets with high affinity and specificity, offering enormous ...

Deep learning segmentation of organs-at-risk with integration into clinical workflow for pediatric brain radiotherapy.

PURPOSE: Radiation therapy (RT) of pediatric brain cancer is known to be associated with long-term n...

Combined substituent number utilized machine learning for the development of antimicrobial agent.

The utilization of machine learning has a potential to improve the environment of the development of...

Nanoinformatics based insights into the interaction of blood plasma proteins with carbon based nanomaterials: Implications for biomedical applications.

In the past three decades, interest in using carbon-based nanomaterials (CBNs) in biomedical applica...

Automated Detection of Pediatric Foreign Body Aspiration from Chest X-rays Using Machine Learning.

OBJECTIVE/HYPOTHESIS: Standard chest radiographs are a poor diagnostic tool for pediatric foreign bo...

Safety of SGLT-2 inhibitors in the management of heart failure in the adult congenital heart disease patient population.

BACKGROUND: Sodium glucose transporter 2 inhibitors (SGLT-2i) have shown safety and efficacy in pati...

Pattern Recognition and Anomaly Detection in fetal morphology using Deep Learning and Statistical learning (PARADISE): protocol for the development of an intelligent decision support system using fetal morphology ultrasound scan to detect fetal congenital anomaly detection.

INTRODUCTION: Congenital anomalies are the most encountered cause of fetal death, infant mortality a...

Computational drug development for membrane protein targets.

The application of computational biology in drug development for membrane protein targets has experi...

Leveraging machine learning to dissect role of combinations of amino acids in modulating the effect of zinc on mammalian cell growth.

Although the contributions of individual components of cell culture media are largely known, their c...

Immunization against inhibin DNA vaccine as an alternative therapeutic for improving follicle development and reproductive performance in beef cattle.

The objective of the present study was to investigate the potential role of immunization against INH...

Machine learning models to evaluate mortality in pediatric patients with pneumonia in the intensive care unit.

OBJECTIVES: This study aimed to predict mortality in children with pneumonia who were admitted to th...

Proceedings From the 2022 ACR-RSNA Workshop on Safety, Effectiveness, Reliability, and Transparency in AI.

Despite the surge in artificial intelligence (AI) development for health care applications, particul...

The State of Artificial Intelligence in Pediatric Surgery: A Systematic Review.

BACKGROUND: Artificial intelligence (AI) has been recently shown to improve clinical workflows and o...

Atrial Septal Defect Detection in Children Based on Ultrasound Video Using Multiple Instances Learning.

Thoracic echocardiography (TTE) can provide sufficient cardiac structure information, evaluate hemod...

Study of Serum Fibroblast Growth Factor 23 as a Predictor of Endothelial Dysfunction among Egyptian Patients with Diabetic Kidney Disease.

Endothelial dysfunction in patients with diabetic nephropathy is caused by nontraditional factors in...

Revolutionizing congenital central hypoventilation syndrome screening: the potential of machine learning approaches.

An artificial intelligence-driven predictive model for pediatric allogeneic hematopoietic stem cell transplantation using clinical variables.

BACKGROUND: Hematopoietic stem cell transplantation (HSCT) is a procedure with high morbidity and mo...

Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk.

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative fo...

Comparing the Quality of Domain-Specific Versus General Language Models for Artificial Intelligence-Generated Differential Diagnoses in PICU Patients.

OBJECTIVES: Generative language models (LMs) are being evaluated in a variety of tasks in healthcare...

Artificial intelligence for drug discovery and development in Alzheimer's disease.

The complex molecular mechanism and pathophysiology of Alzheimer's disease (AD) limits the developme...

White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group.

White matter pathways, typically studied with diffusion tensor imaging (DTI), have been implicated i...