Pediatrics

AAPM task group report 273: Recommendations on best practices for AI and machine learning for computer-aided diagnosis in medical imaging.

Rapid advances in artificial intelligence (AI) and machine learning, and specifically in deep learni...

Hospital crowdedness evaluation and in-hospital resource allocation based on image recognition technology.

How to allocate the existing medical resources reasonably, alleviate hospital congestion and improve...

Deep Learning-Based Multiclass Brain Tissue Segmentation in Fetal MRIs.

Fetal brain tissue segmentation is essential for quantifying the presence of congenital disorders in...

Early experience with low-pass filtered images facilitates visual category learning in a neural network model.

Humans are born with very low contrast sensitivity, meaning that inputs to the infant visual system ...

Ethical considerations of using artificial intelligence to drive clinical decision support in pediatric medical settings.

Artificial intelligence-driven wearable technologies for neonatal cardiorespiratory monitoring: Part 1 wearable technology.

With the development of Artificial Intelligence techniques, smart health monitoring is becoming more...

Considerations for Creating a Restricted Data Environment with Complete Primary Care Electronic Medical Record Data.

Background: Historically, primary care databases have been limited to subsets of the full electronic...

Explainable Machine Learning Model to Predict COVID-19 Severity Among Older Adults in the Province of Quebec.

Context: Patients over the age of 65 years are more likely to experience higher severity and mortali...

High throughput optimization of medium composition for Escherichia coli protein expression using deep learning and Bayesian optimization.

To improve synthetic media for protein expression in Escherichia coli, a strategy using deep neural ...

Deep Learning on Multiphysical Features and Hemodynamic Modeling for Abdominal Aortic Aneurysm Growth Prediction.

Prediction of abdominal aortic aneurysm (AAA) growth is of essential importance for the early treatm...

Painless and accurate medical image analysis using deep reinforcement learning with task-oriented homogenized automatic pre-processing.

Pre-processing is widely applied in medical image analysis to remove the interference information. H...

An accurate deep learning model for wheezing in children using real world data.

Auscultation is an important diagnostic method for lung diseases. However, it is a subjective modali...

Accuracy of computer-assisted pedicle screw placement for adolescent idiopathic scoliosis: a comparison between robotics and navigation.

PURPOSE: To compare the accuracy of pedicle screw placement in adolescent idiopathic scoliosis (AIS)...

Automated quantitative assessment of pediatric blunt hepatic trauma by deep learning-based CT volumetry.

BACKGROUND: To develop an end-to-end deep learning method for automated quantitative assessment of p...

Application of percutaneous nephrolithotomy combined with da Vinci Xi robot in complicated upper urinary tract repair surgery: A case report.

Duplex kidney and ureter is a congenital malformation. Few patients present with hydronephrosis caus...

Game theoretical trajectory planning enhances social acceptability of robots by humans.

Since humans and robots are increasingly sharing portions of their operational spaces, experimental ...

Predicting childhood and adolescent attention-deficit/hyperactivity disorder onset: a nationwide deep learning approach.

Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous disorder with a high degree of ps...

On usage of artificial intelligence for predicting mortality during and post-pregnancy: a systematic review of literature.

BACKGROUND: Care during pregnancy, childbirth and puerperium are fundamental to avoid pathologies fo...

From computer to bedside, involving neonatologists in artificial intelligence models for neonatal medicine.

In recent years, data have become the main driver of medical innovation. With increased availability...

Use of Robot-Assisted Gait Training in Pediatric Patients with Cerebral Palsy in an Inpatient Setting-A Randomized Controlled Trial.

Robot-assisted gait training (RAGT) provides a task-based support of walking using exoskeletons. Evi...

Review of robot-assisted laparoscopic surgery in management of infant congenital urology: Advances and limitations in utilization and learning.

As robotic-assisted (RAL) surgery expanded to treat pediatric congenital disease, infant anatomy and...