Pediatrics

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

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Novel use of deep neural networks on photographic identification of epaulette sharks (Hemiscyllium ocellatum) across life stages.

Photographic identification (photo ID) is an established method that is used to count animals and tr...

Modeling and predicting meat yield and growth performance using morphological features of narrow-clawed crayfish with machine learning techniques.

In recent studies, artificial intelligence and machine learning methods give higher accuracy than ot...

Training and Comparison of nnU-Net and DeepMedic Methods for Autosegmentation of Pediatric Brain Tumors.

BACKGROUND AND PURPOSE: Tumor segmentation is essential in surgical and treatment planning and respo...

Morphological Rule-Constrained Object Detection of Key Structures in Infant Fundus Image.

The detection of optic disc and macula is an essential step for ROP (Retinopathy of prematurity) zon...

SDF4CHD: Generative modeling of cardiac anatomies with congenital heart defects.

Congenital heart disease (CHD) encompasses a spectrum of cardiovascular structural abnormalities, of...

Targeting Machine Learning and Artificial Intelligence Algorithms in Health Care to Reduce Bias and Improve Population Health.

Policy Points Artificial intelligence (AI) is disruptively innovating health care and surpassing our...

Recent progress in artificial intelligence and machine learning for novel diabetes mellitus medications development.

Diabetes mellitus, stemming from either insulin resistance or inadequate insulin secretion, represen...

Differentially Private Client Selection and Resource Allocation in Federated Learning for Medical Applications Using Graph Neural Networks.

Federated learning (FL) has emerged as a pivotal paradigm for training machine learning models acros...

The application of machine learning methods for predicting the progression of adolescent idiopathic scoliosis: a systematic review.

Predicting curve progression during the initial visit is pivotal in the disease management of patien...

Deep Learning-Empowered Clinical Big Data Analytics in Healthcare Digital Twins.

With the rapid development of information technology, great changes have taken place in the way of m...

A YOLOX-Based Deep Instance Segmentation Neural Network for Cardiac Anatomical Structures in Fetal Ultrasound Images.

Echocardiography is an essential procedure for the prenatal examination of the fetus for congenital ...

Emerging Analytical Approaches for Personalized Medicine Using Machine Learning In Pediatric and Congenital Heart Disease.

Precision and personalized medicine, the process by which patient management is tailored to individu...

The circular economy through the prism of machine learning and the YouTube video media platform.

The transition to a Circular Economy (CE) is rapidly gaining ground across countries and industries....

The heart sound classification of congenital heart disease by using median EEMD-Hurst and threshold denoising method.

Heart sound signals are vital for the machine-assisted detection of congenital heart disease. Howeve...

Identifying psychological predictors of SARS-CoV-2 vaccination: A machine learning study.

BACKGROUND: Major barriers to addressing SARS-CoV-2 vaccine hesitancy include limited knowledge of w...

Transforming Health Care Landscapes: The Lever of Radiology Research and Innovation on Emerging Markets Poised for Aggressive Growth.

Advances in radiology are crucial not only to the future of the field but to medicine as a whole. He...

Plastic particles and fluorescent brightener co-modify Chlorella pyrenoidosa photosynthesis and a machine learning approach predict algae growth.

Global release of plastics exerts various impacts on the ecological cycle, particularly on primary p...

Artificial Intelligence for Early Detection of Pediatric Eye Diseases Using Mobile Photos.

IMPORTANCE: Identifying pediatric eye diseases at an early stage is a worldwide issue. Traditional s...

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