Pediatrics

Machine learning paradigm for dynamic contrast-enhanced MRI evaluation of expanding bladder.

Delineation of the bladder under a dynamic contrast enhanced (DCE)-MRI protocol requires robust segm...

Effect of congenital adrenal hyperplasia treated by glucocorticoids on plasma metabolome: a machine-learning-based analysis.

BACKGROUND: Congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency leads to impaired ...

Envisioning Insight-Driven Learning Based on Thick Data Analytics With Focus on Healthcare.

Detecting and analyzing patient insights from social media enables healthcare givers to better under...

Pediatric Acute-Onset Neuropsychiatric Syndrome: A Data Mining Approach to a Very Specific Constellation of Clinical Variables.

Pediatric acute onset neuropsychiatric syndrome (PANS) is a clinically heterogeneous disorder prese...

Smart Environments and Social Robots for Age-Friendly Integrated Care Services.

The world is facing major societal challenges because of an aging population that is putting increas...

Anatomical pathology (human structural biopathology) in the era of "Big Data", digitalization, 5G and artificial intelligence: Evolution or Revolution?

A proposal of an updated system of the Organization of Scientific Biomedical Kowledge is presented, ...

Parametric investigation of the effects of load level on fatigue crack growth in trabecular bone based on artificial neural network computation.

This study reports the development of an artificial neural network computation model to predict the ...

Machine Learning to Support Hemodynamic Intervention in the Neonatal Intensive Care Unit.

Hemodynamic support in neonatal intensive care is directed at maintaining cardiovascular wellbeing. ...

Multi-instance Deep Learning of Ultrasound Imaging Data for Pattern Classification of Congenital Abnormalities of the Kidney and Urinary Tract in Children.

OBJECTIVE: To reliably and quickly diagnose children with posterior urethral valves (PUV), we develo...

Artificial Intelligence-Empowered Mobilization of Assessments in COVID-19-like Pandemics: A Case Study for Early Flattening of the Curve.

The global outbreak of the Coronavirus Disease 2019 (COVID-19) pandemic has uncovered the fragility ...

A systematic machine learning and data type comparison yields metagenomic predictors of infant age, sex, breastfeeding, antibiotic usage, country of origin, and delivery type.

The microbiome is a new frontier for building predictors of human phenotypes. However, machine learn...

Enhancing the Surface Properties of a Bioengineered Anterior Cruciate Ligament Matrix for Use with Point-of-Care Stem Cell Therapy.

We have previously developed a poly(-lactic) acid (PLLA) bioengineered anterior cruciate ligament (A...

Prediction of chronological and biological age from laboratory data.

Aging has pronounced effects on blood laboratory biomarkers used in the clinic. Prior studies have l...

Development, Implementation, and Evaluation of a Personalized Machine Learning Algorithm for Clinical Decision Support: Case Study With Shingles Vaccination.

BACKGROUND: Although clinical decision support (CDS) alerts are effective reminders of best practice...

Deep learning in congenital heart disease imaging: hope but not haste.

Ependymoma and pilocytic astrocytoma: Differentiation using radiomics approach based on machine learning.

Mandatory accurate and specific diagnosis demands have brought about increased challenges for radiol...

Caregiver perspectives on a smart home-based socially assistive robot for individuals with Alzheimer's disease and related dementia.

: Innovative assistive technology can address aging-in-place and caregiving needs of individuals wit...

Robot-Assisted Laparoscopic Urachal Excision Using Hidden Incision Endoscopic Surgery Technique in Pediatric Patients.

Although laparoscopic urachal excision in children has been well reported, there are limited data o...

Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980-2015.

Quantification of stillbirth risk has potential to support clinical decision-making. Studies that ha...

Prediction of admission in pediatric emergency department with deep neural networks and triage textual data.

Emergency department (ED) overcrowding is a global condition that severely worsens attention to pati...

Identifying predictive features of autism spectrum disorders in a clinical sample of adolescents and adults using machine learning.

Diagnosing autism spectrum disorders (ASD) is a complicated, time-consuming process which is particu...