Pediatrics

Automated detection of cribriform growth patterns in prostate histology images.

Cribriform growth patterns in prostate carcinoma are associated with poor prognosis. We aimed to int...

Quantitative retrospective natural history modeling for orphan drug development.

The natural history of most rare diseases is incompletely understood and usually relies on studies w...

Comparison of Conventional Statistical Methods with Machine Learning in Medicine: Diagnosis, Drug Development, and Treatment.

Futurists have anticipated that novel autonomous technologies, embedded with machine learning (ML), ...

Development, implementation, and prospective validation of a model to predict 60-day end-of-life in hospitalized adults upon admission at three sites.

BACKGROUND: Automated systems that use machine learning to estimate a patient's risk of death are be...

Improving preoperative risk-of-death prediction in surgery congenital heart defects using artificial intelligence model: A pilot study.

BACKGROUND: Congenital heart disease accounts for almost a third of all major congenital anomalies. ...

Towards predictive neural network dynamical theory: Comment on "The growth of cognition: Free energy minimization and the embryogenesis of cortical computation" by Wright and Bourke.

Development and clinical implementation of tailored image analysis tools for COVID-19 in the midst of the pandemic: The synergetic effect of an open, clinically embedded software development platform and machine learning.

PURPOSE: During the emerging COVID-19 pandemic, radiology departments faced a substantial increase i...

Machine learning based refined differential gene expression analysis of pediatric sepsis.

BACKGROUND: Differential expression (DE) analysis of transcriptomic data enables genome-wide analysi...

A machine-learning algorithm for neonatal seizure recognition: a multicentre, randomised, controlled trial.

BACKGROUND: Despite the availability of continuous conventional electroencephalography (cEEG), accur...

Deep learning for neonatal seizure detection: a friend rather than foe.

Using Machine Learning to Train a Wearable Device for Measuring Students' Cognitive Load during Problem-Solving Activities Based on Electrodermal Activity, Body Temperature, and Heart Rate: Development of a Cognitive Load Tracker for Both Personal and Classroom Use.

Automated tracking of physical fitness has sparked a health revolution by allowing individuals to tr...

A machine learning approach to predict intravenous immunoglobulin resistance in Kawasaki disease patients: A study based on a Southeast China population.

Kawasaki disease is the leading cause of pediatric acquired heart disease. Coronary artery abnormali...

A Framework for User Adaptation and Profiling for Social Robotics in Rehabilitation.

Physical rehabilitation therapies for children present a challenge, and its success-the improvement ...

Investigating plant uptake of organic contaminants through transpiration stream concentration factor and neural network models.

Uptake of seven organic contaminants including bisphenol A, estriol, 2,4-dinitrotoluene, N,N-diethyl...

From Patient Engagement to Precision Oncology: Leveraging Informatics to Advance Cancer Care.

OBJECTIVES: Conduct a survey of the literature for advancements in cancer informatics over the last ...

Educational Value of YouTube Surgical Videos of Pediatric Robot-Assisted Laparoscopic Pyeloplasty: A Qualitative Assessment.

Surgeons and residents report using videos to prepare for procedures, with a preference for open ac...

High tissue contrast image synthesis via multistage attention-GAN: Application to segmenting brain MR scans.

Magnetic resonance imaging (MRI) presents a detailed image of the internal organs via a magnetic fie...

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model.

Machine learning (ML) algorithms permit the integration of different features into a model to perfor...

Machine Learning Models to Predict Childhood and Adolescent Obesity: A Review.

The prevalence of childhood and adolescence overweight an obesity is raising at an alarming rate in ...

Reconfiguration of αmplitude driven dominant coupling modes (DoCM) mediated by α-band in adolescents with schizophrenia spectrum disorders.

Electroencephalography (EEG) based biomarkers have been shown to correlate with the presence of psyc...

Deep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional Study.

BACKGROUND AND PURPOSE: Posterior fossa tumors are the most common pediatric brain tumors. MR imagin...