Pediatrics

Artificial Intelligence for Personalized Preventive Adolescent Healthcare.

Recent advances in artificial intelligence (AI) are creating new opportunities for personalizing technology-based health interventions to adolescents. This article provides a computer science perspective on how emerging AI technologies-intelligent learning environments, interactive narrative generation, user modeling, and adaptive coaching-can be utilized to model adolescent learning and engagemen...

Risk assessment for intra-abdominal injury following blunt trauma in children: Derivation and validation of a machine learning model.

BACKGROUND: Computed tomography is the criterion standard for diagnosing intra-abdominal injury (IAI) but is expensive and risks radiation exposure. The Pediatric Emergency Care Applied Research Network (PECARN) model identifies children at low risk of IAI requiring intervention (IAI-I) in whom computed tomography may be omitted but does not provide an individualized risk assessment to positively ...

Automatic Machine Learning to Differentiate Pediatric Posterior Fossa Tumors on Routine MR Imaging.

BACKGROUND AND PURPOSE: Differentiating the types of pediatric posterior fossa tumors on routine imaging may help in preoperative evaluation and guide...

Wavelet Spectral Deep-training of Convolutional Neural Networks for Accurate Identification of High-Frequency Micro-Scale Spike Transients in the Post-Hypoxic-Ischemic EEG of Preterm Sheep.

Early diagnosis and prognosis of babies with signs of hypoxic-ischemic encephalopathy (HIE) is currently limited and requires reliable prognostic biom...

Potential Prognostic Markers in the Heart Rate Variability Features for Early Diagnosis of Sepsis in the Pediatric Intensive Care Unit using Convolutional Neural Network Classifiers.

Blood infection due to different circumstances could immediately develop to an extreme body reaction that leads to a serious life-threatening conditio...

Wavelet Spectral Time-Frequency Training of Deep Convolutional Neural Networks for Accurate Identification of Micro-Scale Sharp Wave Biomarkers in the Post-Hypoxic-Ischemic EEG of Preterm Sheep.

Neonatal hypoxic-ischemic encephalopathy (HIE) evolves over different phases of time during recovery. Some neuroprotection treatments are only effecti...

Multi-View Ensemble Convolutional Neural Network to Improve Classification of Pneumonia in Low Contrast Chest X-Ray Images.

Pneumonia is one of the leading causes of childhood mortality worldwide. Chest x-ray (CXR) can aid the diagnosis of pneumonia, but in the case of low ...

Deep transfer learning for video-based detection of newborn presence in incubator.

Preterm newborns are prone to late-onset sepsis, leading to a high risk of mortality. Video-based analysis of motion is a promising non-invasive appro...

Automated Assessment System for Neonatal Endotracheal Intubation Using Dilated Convolutional Neural Network.

Neonatal endotracheal intubation (ETI) is an important, complex resuscitation skill, which requires a significant amount of practice to master. Curren...

Potential Prognostic Markers in the Heart Rate Variability Features for Early Diagnosis of Sepsis in the Pediatric Intensive Care Unit using Convolutional Neural Network Classifiers.

Blood infection due to different circumstances could immediately develop to an extreme body reaction that leads to a serious life-threatening conditio...

Identifying tracé alternant activity in neonatal EEG using an inter-burst detection approach.

Electroencephalography (EEG) is an important clinical tool for reviewing sleep-wake cycling in neonates in intensive care. Tracé alternant (TA)-a char...

Design, Control, and Simulation of a Neonatal Incubator.

In this project, a fully functional incubator with precise control with respect to temperature, humidity, and airflow was developed and assessed. In p...

Evaluation of Different Learning Algorithms of Neural Networks for Drug Dosing Recommendations in Pediatrics.

Publicly accessible databases with evidence-based information on drug dosages for children and adolescents are not available in Germany. In previous w...

Commercial Adoption of AI in the Healthcare Sector: An Exploratory Analysis of S&P500 Companies.

The use of Artificial Intelligence (AI) technologies within the healthcare sector is growing. However, there are differences in the speed of commercia...

Investigating the Barriers to Physician Adoption of an Artificial Intelligence- Based Decision Support System in Emergency Care: An Interpretative Qualitative Study.

The development of artificial intelligence (AI) systems to support diagnostic decision-making is rapidly expanding in health care. However, important ...

Integrating Socially Assistive Robots into Japanese Nursing Care.

This paper presents experiences of integrating assistive robots in Japanese nursing care through semi-structured interviews and site observations at t...

Rigid Cranial Fixation for Robot-Assisted Stereoelectroencephalography in Toddlers: Technical Considerations.

BACKGROUND: Stereoelectroencephalography (sEEG) using depth electrodes has become a mainstay of pediatric epilepsy surgery. This technique relies on r...

Development of an Alarm Algorithm, With Nanotechnology Multimodal Sensor, to Predict Impending Infusion Failure and Improve Safety of Peripheral Intravenous Catheters in Neonates.

BACKGROUND: Peripheral intravenous catheters connected to an infusion pump are necessary for the delivery of fluids, nutrition, and medications to hos...

Augmented intelligence in pediatric anesthesia and pediatric critical care.

PURPOSE OF REVIEW: Acute care technologies, including novel monitoring devices, big data, increased computing capabilities, machine-learning algorithm...

Machine Learning and Artificial Intelligence in Pediatric Research: Current State, Future Prospects, and Examples in Perioperative and Critical Care.