Pediatrics

Complex population dynamics in a spatial microbial ecosystem with Physarum polycephalum.

This research addresses the interactions between the unicellular slime mold Physarum polycephalum and a red yeast in a spatial ecosystem over week-long imaging experiments. An inverse relationship between the growth rates of both species is shown, where P. polycephalum has positive growth when the red yeast has a negative growth rate and vice versa. The data also captures successional and oscillat...

Robotics and future technical developments in pediatric urology.

Minimally invasive surgery (MIS) has represented the main innovation in the field of pediatric surgery and urology over the last 30 years. Pediatric MIS is a wide field, ranging from the standard laparoscopic surgery using 3-mm ports to robotics mainly adopted for pediatric urology indications. The aim of this paper was to summarize the current status of robotic surgery in pediatric urology and to...

High through-plane resolution CT imaging with self-supervised deep learning.

CT images for radiotherapy planning are usually acquired in thick slices to reduce the imaging dose, especially for pediatric patients, and to lessen ...

Accuracy of Asthma Computable Phenotypes to Identify Pediatric Asthma at an Academic Institution.

OBJECTIVES: Asthma is a heterogenous condition with significant diagnostic complexity, including variations in symptoms and temporal criteria. The dis...

Initial Experience with Robotic Inguinal Hernia Repair in the Adolescent Population.

There is no one standard procedure encompassing the needs and differences of the entire pediatric population for inguinal hernia repair (IHR). Severa...

Detecting lumbar lesions in Tc-MDP SPECT by deep learning: Comparison with physicians.

PURPOSE: Tc-MDP single-photon emission computed tomography (SPECT) is an established tool for diagnosing lumbar stress, a common cause of low back pa...

Stability of Compounded Digoxin Solution 0.05 mg/mL for Injection.

In 2015, commercial pediatric digoxin injection 0.05 mg/mL was discontinued, leaving only one adult concentration (0.25 mg/mL) for injection on the C...

Application of a deep learning image reconstruction (DLIR) algorithm in head CT imaging for children to improve image quality and lesion detection.

BACKGROUND: To evaluate the performance of a Deep Learning Image Reconstruction (DLIR) algorithm in pediatric head CT for improving image quality and ...

Bayesian convolutional neural network estimation for pediatric pneumonia detection and diagnosis.

BACKGROUND AND OBJECTIVES: Pneumonia is a disease that affects the lungs, making breathing difficult. Nowadays, pneumonia is the disease that kills th...

Evaluation of pediatric hydronephrosis using deep learning quantification of fluid-to-kidney-area ratio by ultrasonography.

PURPOSE: Hydronephrosis is the dilation of the pelvicalyceal system due to the urine flow obstruction in one or both kidneys. Conventionally, renal pe...

Optimizing COVID-19 vaccine distribution across the United States using deterministic and stochastic recurrent neural networks.

Optimizing COVID-19 vaccine distribution can help plan around the limited production and distribution of vaccination, particularly in early stages. On...

Artificial intelligence reporting guidelines: what the pediatric radiologist needs to know.

There has been an exponential rise in artificial intelligence (AI) research in imaging in recent years. While the dissemination of study data that has...

Hyperspectral imaging and deep learning for quantification of Clostridium sporogenes spores in food products using 1D- convolutional neural networks and random forest model.

Clostridium sporogenes spores are used as surrogates for Clostridium botulinum, to verify thermal exposure and lethality in sterilization regimes by f...

Risk prediction for delayed clearance of high-dose methotrexate in pediatric hematological malignancies by machine learning.

This study aimed to establish a predictive model to identify children with hematologic malignancy at high risk for delayed clearance of high-dose meth...

Automatic Detection and Classification of Multiple Catheters in Neonatal Radiographs with Deep Learning.

We develop and evaluate a deep learning algorithm to classify multiple catheters on neonatal chest and abdominal radiographs. A convolutional neural n...

Flexibility in Drug Product Development: A Perspective.

The process of bringing a drug to market involves innumerable decisions to refine a concept into a final product. The final product goes through exten...

Choquet fuzzy integral-based classifier ensemble technique for COVID-19 detection.

The COVID-19 outbreak has resulted in a global pandemic and led to more than a million deaths to date. COVID-19 early detection is essential for its m...

A Typology of Existing Machine Learning-Based Predictive Analytic Tools Focused on Reducing Costs and Improving Quality in Health Care: Systematic Search and Content Analysis.

BACKGROUND: Considerable effort has been devoted to the development of artificial intelligence, including machine learning-based predictive analytics ...

Detecting neonatal acute bilirubin encephalopathy based on T1-weighted MRI images and learning-based approaches.

BACKGROUND: Neonatal hyperbilirubinemia is a common clinical condition that requires medical attention in newborns, which may develop into acute bilir...

Deep learning for classification of pediatric chest radiographs by WHO's standardized methodology.

BACKGROUND: The World Health Organization (WHO)-defined radiological pneumonia is a preferred endpoint in pneumococcal vaccine efficacy and effectiven...