Pediatrics

Latest AI and machine learning research in pediatrics for healthcare professionals.

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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...

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 ...

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...

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 obstructio...

Ethical Artificial Intelligence in Chemical Research and Development: A Dual Advantage for Sustainability.

Artificial intelligence can be a game changer to address the global challenge of humanity-threatenin...

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 distributio...

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 yea...

AI-based language models powering drug discovery and development.

The discovery and development of new medicines is expensive, time-consuming, and often inefficient, ...

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...

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 a...

Flexibility in Drug Product Development: A Perspective.

The process of bringing a drug to market involves innumerable decisions to refine a concept into a f...

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 dat...

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 attenti...

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 endpoi...

Robot assisted laser-interstitial thermal therapy with iSYS1 and Visualase: how I do it.

BACKGROUND: Laser-interstitial thermal therapy (LITT) is an ablative treatment based on a surgically...

Remote Care Assistance in Emergency Department Based on Smart Medical.

Smart medical care is user-centric, medical information is the main line, and big data, Internet of ...

Prediction and Early Warning of Regional Coordinated Development Based on Convolution Neural Network Algorithm.

In order to respond to the regional coordinated development of the country, it is necessary to put f...

Adversarial attack vulnerability of medical image analysis systems: Unexplored factors.

Adversarial attacks are considered a potentially serious security threat for machine learning system...

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