Pediatrics

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

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Preterm Newborn Presence Detection in Incubator and Open Bed Using Deep Transfer Learning.

Video-based motion analysis recently appeared to be a promising approach in neonatal intensive care ...

Novel AI driven approach to classify infant motor functions.

The past decade has evinced a boom of computer-based approaches to aid movement assessment in early ...

Development and Validation of Machine Learning Models to Predict Admission From Emergency Department to Inpatient and Intensive Care Units.

STUDY OBJECTIVE: This study aimed to develop and validate 2 machine learning models that use histori...

Totally robotic intracorporeal Monti-Yang continent ileovesicostomy in patient with previous robotic surgery-Technique description.

We present a video case report of a pediatric patient with previous robotic abdominal surgery who un...

A Zwitterionic-Aromatic Motif-Based ionic skin for highly biocompatible and Glucose-Responsive sensor.

Electronic skins that can sense external stimuli have been of great significance in artificial intel...

Medical Specialty Recommendations by an Artificial Intelligence Chatbot on a Smartphone: Development and Deployment.

BACKGROUND: The COVID-19 pandemic has limited daily activities and even contact between patients and...

Well-rounded devices: the fabrication of electronics on curved surfaces - a review.

With the arrival of the internet of things and the rise of wearable computing, electronics are playi...

Aiding clinical assessment of neonatal sepsis using hematological analyzer data with machine learning techniques.

INTRODUCTION: Early diagnosis and antibiotic administration are essential for reducing sepsis morbid...

Development and Validation of a Machine Learning Model Using Administrative Health Data to Predict Onset of Type 2 Diabetes.

IMPORTANCE: Systems-level barriers to diabetes care could be improved with population health plannin...

Development of a Method for Clinical Evaluation of Artificial Intelligence-Based Digital Wound Assessment Tools.

IMPORTANCE: Accurate assessment of wound area and percentage of granulation tissue (PGT) are importa...

Digital Twins for Multiple Sclerosis.

An individualized innovative disease management is of great importance for people with multiple scle...

Applications of Machine Learning in Solid Oral Dosage Form Development.

This review comprehensively summarizes the application of machine learning in solid oral dosage form...

Synthetic Database of Aortic Morphometry and Hemodynamics: Overcoming Medical Imaging Data Availability.

Modeling of hemodynamics and artificial intelligence have great potential to support clinical diagno...

Artificial intelligence for clinical oncology.

Clinical oncology is experiencing rapid growth in data that are collected to enhance cancer care. Wi...

Adverse Outcomes Prediction for Congenital Heart Surgery: A Machine Learning Approach.

OBJECTIVE: Risk assessment tools typically used in congenital heart surgery (CHS) assume that variou...

Diagnosing Atrial Septal Defect from Electrocardiogram with Deep Learning.

The heart murmur associated with atrial septal defects is often faint and can thus only be detected ...

Growth strategy determines the memory and structural properties of brain networks.

The interplay between structure and function affects the emerging properties of many natural systems...

Development Issues of Healthcare Robots: Compassionate Communication for Older Adults with Dementia.

Although progress is being made in affective computing, issues remain in enabling the effective expr...

Task-sharing with artificial intelligence: a design hypothesis for an Emergency Unit in sub-Saharan Africa.

In sub-Saharan Africa, there is a significant unmet need for emergency care, with a shortage of trai...

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