Pediatrics

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

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[Pharmacological knowledge bases in Sweden: successes and future in a time of information overflow].

Skewed information about medicines in social media influence the healthcare-patient contact. Healthc...

Using deep learning and electronic health records to detect Noonan syndrome in pediatric patients.

PURPOSE: The variable expressivity and multisystem features of Noonan syndrome (NS) make it difficul...

Performance comparison of three deep learning models for impacted mesiodens detection on periapical radiographs.

This study aimed to develop deep learning models that automatically detect impacted mesiodens on per...

Digital Transformation and Financial Risk Prediction of Listed Companies.

Digitalization is a revolution, a frontal battleground in the new global competitive landscape, and ...

Is primary health care ready for artificial intelligence? What do primary health care stakeholders say?

BACKGROUND: Effective deployment of AI tools in primary health care requires the engagement of pract...

Application of GIS Technology-Supported Cross Media Fusion Method Based on Deep Learning in Landscape Performance Evaluation.

GIS technology can provide reasonable and sustainable data support for landscape planning and ecolog...

Public Discourse and Sentiment Toward Dementia on Chinese Social Media: Machine Learning Analysis of Weibo Posts.

BACKGROUND: Dementia is a global public health priority due to rapid growth of the aging population....

Design of Psychological Well-Being Education Environment Scheme Based on Deep Learning Theory.

This paper discusses the structure of psychological well-being education programmes in higher educat...

An Automated View Classification Model for Pediatric Echocardiography Using Artificial Intelligence.

BACKGROUND: View classification is a key step toward building a fully automated system for interpret...

Empirical Analysis of Early Childhood Enlightenment Education Using Neural Network.

This exploration aims to study the value orientation and essence of early childhood enlightenment ed...

Deep Learning to Predict Geographic Atrophy Area and Growth Rate from Multimodal Imaging.

OBJECTIVE: To develop deep learning models for annualized geographic atrophy (GA) growth rate predic...

Real-Time Prediction of Growth Characteristics for Individual Fruits Using Deep Learning.

Understanding the growth status of fruits can enable precise growth management and improve the produ...

Adolescent Depression Detection Model Based on Multimodal Data of Interview Audio and Text.

Depression is a common mental disease that has a tendency to develop at a younger age. Early detecti...

Balancing national economic policy outcomes for sustainable development.

The 2030 Sustainable Development Goals (SDGs) aim at jointly improving economic, social, and environ...

Machine learning-assisted discovery of growth decision elements by relating bacterial population dynamics to environmental diversity.

Microorganisms growing in their habitat constitute a complex system. How the individual constituents...

Development and application of a fuzzy occupational health risk assessment model in the healthcare industry.

BACKGROUND: Hazards of the workplace and their impacts on the healthcare industry affect the quality...

Evaluation algorithm of coastal city ecological civilization development level based on improved BP neural network.

To accurately evaluate the development level of ecological civilization in coastal cities, this pape...

A deep learning pipeline for the automated segmentation of posterior limb of internal capsule in preterm neonates.

Segmentation of specific brain tissue from MRI volumes is of great significance for brain disease di...

Frameless robot-assisted stereotactic biopsy: an effective and minimally invasive technique for pediatric diffuse intrinsic pontine gliomas.

PURPOSE: Diffuse intrinsic pontine gliomas (DIPGs) are prone to high surgical risks, and they could ...

The requirements for performing artificial-intelligence-related research and model development.

Artificial intelligence research in health care has undergone tremendous growth in the last several ...

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