Pediatrics

Vaxign2: the second generation of the first Web-based vaccine design program using reverse vaccinology and machine learning.

Vaccination is one of the most significant inventions in medicine. Reverse vaccinology (RV) is a state-of-the-art technique to predict vaccine candidates from pathogen's genome(s). To promote vaccine development, we updated Vaxign2, the first web-based vaccine design program using reverse vaccinology with machine learning. Vaxign2 is a comprehensive web server for rational vaccine design, consisti...

Machine Learning: The Next Paradigm Shift in Medical Education.

Machine learning (ML) algorithms are powerful prediction tools with immense potential in the clinical setting. There are a number of existing clinical tools that use ML, and many more are in development. Physicians are important stakeholders in the health care system, but most are not equipped to make informed decisions regarding deployment and application of ML technologies in patient care. It is...

Towards real-time diagnosis for pediatric sepsis using graph neural network and ensemble methods.

OBJECTIVE: The rapid onset of pediatric sepsis and the short optimal time for resuscitation pose a severe threat to children's health in the ICU. Time...

Artificial intelligence technologies empowering identification of novel diagnostic molecular markers in gastric cancer.

In recent clinical practice the molecular diagnostics have been significantly empowered and upgraded by the use of Artificial Intelligence and its ass...

Machine learning modeling of the effects of media formulated with various yeast extracts on heterologous protein production in Escherichia coli.

In microbial manufacturing, yeast extract is an important component of the growth media. The production of heterologous proteins often varies because ...

Predicting in-hospital mortality in ICU patients with sepsis using gradient boosting decision tree.

Sepsis is a leading cause of mortality in the intensive care unit. Early prediction of sepsis can reduce the overall mortality rate and cost of sepsis...

Artificial Intelligence in Spine Care.

Artificial intelligence is an exciting and growing field in medicine to assist in the proper diagnosis of patients. Although the use of artificial int...

Deep learning for detecting congenital heart disease in the fetus.

[Application of the artificial intelligence-rapid whole-genome sequencing diagnostic system in the neonatal/pediatric intensive care unit].

Pediatric patients in the neonatal intensive care unit (NICU) and the pediatric intensive care unit (PICU) have a high incidence rate of genetic disea...

Use of Artificial Intelligence in Dentistry: Current Clinical Trends and Research Advances.

The field of artificial intelligence (AI) has experienced spectacular development and growth over the past two decades. With recent progress in digiti...

[Current status and trends of pediatric pathology based on artificial intelligence analysis].

Avoidable Serum Potassium Testing in the Cardiac ICU: Development and Testing of a Machine-Learning Model.

OBJECTIVES: To create a machine-learning model identifying potentially avoidable blood draws for serum potassium among pediatric patients following ca...

Brain views that benefit from three-dimensional ultrasound.

PURPOSE OF REVIEW: Fetal central nervous system malformations are among the most common congenital anomalies. Whereas simple axial views are sufficien...

Predicting outcomes in central venous catheter salvage in pediatric central line-associated bloodstream infection.

OBJECTIVE: Central line-associated bloodstream infections (CLABSIs) are a common, costly, and hazardous healthcare-associated infection in children. I...

Swarming behavior and in vivo monitoring of enzymatic nanomotors within the bladder.

Enzyme-powered nanomotors are an exciting technology for biomedical applications due to their ability to navigate within biological environments using...

Applications of Artificial Intelligence for Retinopathy of Prematurity Screening.

OBJECTIVES: Childhood blindness from retinopathy of prematurity (ROP) is increasing as a result of improvements in neonatal care worldwide. We evaluat...

AI-Driven Growth of DSOs.

DSOs have been at the forefront of adopting technology that demonstrates value-add to their businesses. Hence, DSOs have been quick to identify artifi...

Clinical applications of artificial intelligence and machine learning-based methods in inflammatory bowel disease.

Our objective was to review and exemplify how selected applications of artificial intelligence (AI) might facilitate and improve inflammatory bowel di...

The Human Phenotype Ontology in 2021.

The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computational...

Machine Learning Applied to Registry Data: Development of a Patient-Specific Prediction Model for Blood Transfusion Requirements During Craniofacial Surgery Using the Pediatric Craniofacial Perioperative Registry Dataset.

BACKGROUND: Craniosynostosis is the premature fusion of ≥1 cranial sutures and often requires surgical intervention. Surgery may involve extensive ost...