AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Infant

Showing 161 to 170 of 878 articles

Clear Filters

The diagnostic value of artificial intelligence-assisted imaging for developmental dysplasia of the hip: a systematic review and meta-analysis.

Journal of orthopaedic surgery and research
OBJECTIVE: To clarify the efficacy of artificial intelligence (AI)-assisted imaging in the diagnosis of developmental dysplasia of the hip (DDH) through a meta-analysis.

Application of machine-learning models to predict the ganciclovir and valganciclovir exposure in children using a limited sampling strategy.

Antimicrobial agents and chemotherapy
Intravenous ganciclovir and oral valganciclovir display significant variability in ganciclovir pharmacokinetics, particularly in children. Therapeutic drug monitoring currently relies on the area under the concentration-time (AUC). Machine-learning (...

Exploring the determinants of under-five mortality and morbidity from infectious diseases in Cambodia-a traditional and machine learning approach.

Scientific reports
Cambodia has made progress in reducing the under-five mortality rate and burden of infectious diseases among children over the last decades. However the determinants of child mortality and morbidity in Cambodia is not well understood, and no recent a...

Development and testing of a deep learning algorithm to detect lung consolidation among children with pneumonia using hand-held ultrasound.

PloS one
BACKGROUND AND OBJECTIVES: Severe pneumonia is the leading cause of death among young children worldwide, disproportionately impacting children who lack access to advanced diagnostic imaging. Here our objectives were to develop and test the accuracy ...

Risk factors for the time to development of retinopathy of prematurity in premature infants in Iran: a machine learning approach.

BMC ophthalmology
BACKGROUND: Retinopathy of prematurity (ROP), is a preventable leading cause of blindness in infants and is a condition in which the immature retina experiences abnormal blood vessel growth. The development of ROP is multifactorial; nevertheless, the...

Development of an equation to predict delta bilirubin levels using machine learning.

Clinica chimica acta; international journal of clinical chemistry
OBJECTIVE: Delta bilirubin (albumin-covalently bound bilirubin) may provide important clinical utility in identifying impaired hepatic excretion of conjugated bilirubin, but it cannot be measured in real-time for diagnostic purposes in clinical labor...

Investigation of emergency department abandonment rates using machine learning algorithms in a single centre study.

Scientific reports
A critical problem that Emergency Departments (EDs) must address is overcrowding, as it causes extended waiting times and increased patient dissatisfaction, both of which are immediately linked to a greater number of patients who leave the ED early, ...

Using a Disentangled Neural Network to Objectively Assess the Outcomes of Midfacial Surgery in Syndromic Craniosynostosis.

Plastic and reconstructive surgery
BACKGROUND: Advancements in artificial intelligence and the development of shape models that quantify normal head shape and facial morphology provide frameworks by which the outcomes of craniofacial surgery can be compared. In this work, the authors ...